Copyright by Hayley Jeanne Loblein 2019
Transcript of Copyright by Hayley Jeanne Loblein 2019
Copyright
by
Hayley Jeanne Loblein
2019
The Dissertation Committee for Hayley Jeanne Loblein Certifies that this is the approved version of the following Dissertation
Anxiety in Pediatric Epilepsy:
The Role of Stigma and Illness Cognitions
Committee: Timothy Keith, Supervisor Jeffrey Titus, Co-Supervisor Sarah Kate Bearman Stephanie Cawthon
Anxiety in Pediatric Epilepsy:
The Role of Stigma and Illness Cognitions
by
Hayley Jeanne Loblein
Dissertation
Presented to the Faculty of the Graduate School of
The University of Texas at Austin
in Partial Fulfillment
of the Requirements
for the Degree of
Doctor of Philosophy
The University of Texas at Austin
August 2019
Dedication
I would like to dedicate this manuscript to all of the parents and children who I have worked
with during graduate school. I would particularly like to thank the families from the
Pediatric Neuropsychology Clinic at Dell Children’s Medical Center and the anxiety study
at the Texas Child Study Center. You are the inspiration for my research. I hope that I can
continue to engage in research that is meaningful and helpful to the families with whom I
work.
v
Acknowledgements
First, I would like to thank my dissertation committee. Your contributions to my
dissertation and my overall graduate school career are immeasurable. Dr. Titus, it’s hard
to put into words how much I appreciate your guidance and support over these past two
years as a clinical and research supervisor. Thank you for the countless hours you have
spent helping me find a way to merge my clinical and research interests. You have
challenged me, laughed with me, and empowered me; I have walked away from every
supervision energized and prepared to take on anything. I hope that one day I can be the
type of mentor that you have been to me. Dr. Keith, thank you for your support from the
first day of classes until my defense. I hope that one day I can lead in such a calm and
reassuring way. Dr. Bearman, thank you so much for your advice and guidance through all
aspects of my graduate school journey. I hope that one day I can be as dedicated as you are
to promoting evidence-based practices. Dr. Cawthon, your enthusiasm and commitment to
engaging students in their learning and research was palpable from when I first met you on
interview day. I hope that one day I will be able to inspire and energize students in such an
effective way.
I would also like to thank my cohort. Abigail, Ashlee, Becca, Danika, Duncan, and
Josh, you’ve kept me sane through every graduate school hurdle. I’m so lucky to have met
such a wonderful group of people who will be life-long friends and colleagues.
Finally, I would like to thank my family. Mom, Dad, Chaz, and Chelsea, your
support and encouragement have always inspired me to achieve more. And to Brandon, my
partner, thank you for moving to Austin to support me in graduate school and for reminding
me to laugh along the way.
vi
Abstract
Anxiety in Pediatric Epilepsy:
The Role of Stigma and Illness Cognitions
Hayley Jeanne Loblein, Ph.D.
The University of Texas at Austin, 2019
Supervisors: Timothy Keith & Jeffrey Titus
Youth with epilepsy are at an increased risk for developing anxiety when compared
to healthy youth (Alwash, Hussein, & Matloub, 2000; Jones et al., 2007; Russ et al., 2012)
and when compared to youth with other chronic health conditions (Pinquart & Shen, 2011).
Parents have become a significant focus of research examining the environmental risk and
protective factors for anxiety in healthy children (Creswell, Murray, & Cooper, 2011;
Gregory & Eley, 2007), and this is an area of growing research in youth with epilepsy
(Jones & Reilly, 2016; Rodenburg, Meijer, Dekovic, & Aldenkamp, 2006; Schraegle &
Titus, 2017a). The following study aimed to examine the medical and psychosocial risk
factors for anxiety in youth with epilepsy.
Participants included 121 children and adolescents with epilepsy at a tertiary
outpatient clinic in Central Texas who were referred by their neurologists for a
neuropsychological evaluation to assist with treatment planning. Parent perceptions of
stigma and parent illness cognitions were examined to determine their relationship with
parent report of anxiety, seizure-related variables, and parent history of psychopathology.
vii
Using multiple regression, parent perceptions of stigma were a statistically significant
predictor of parent reported child anxiety. Additional moderation analysis suggested that
there is an interaction between parent perceptions of stigma and seizure severity; at higher
levels of seizure severity, higher parent perceptions of stigma were related to higher parent
reported features of anxiety. This suggests the potential for parent perceptions of stigma to
play an important role in anxiety in pediatric epilepsy, particularly in the context of high
seizure severity. Additionally, parent perceptions of stigma, parent illness cognitions, and
parent reported child anxiety were all related to parent reported quality of life, suggesting
the importance of addressing these psychosocial factors to improve quality of life in youth
with epilepsy.
viii
Table of Contents
List of Tables ................................................................................................................. xi
List of Figures ............................................................................................................... xii
Chapter 2: Literature Review ........................................................................................... 6
Epilepsy .................................................................................................................... 6
Incidence, prevalence, cost, and burden of pediatric epilepsy ............................ 7
Etiology ............................................................................................................ 8
Diagnosis .......................................................................................................... 8
Classification .................................................................................................... 8
Treatment of epilepsy ..................................................................................... 12
Outcomes and quality of life in epilepsy ......................................................... 14
Anxiety ................................................................................................................... 20
Prevalence ...................................................................................................... 23
Diagnosis ........................................................................................................ 23
Risk and protective factors .............................................................................. 25
Treatment of anxiety ....................................................................................... 35
Quality of life in anxiety ................................................................................. 36
Anxiety in Pediatric Epilepsy .................................................................................. 37
The forgotten disorder .................................................................................... 37
Prevalence of anxiety in epilepsy .................................................................... 38
Risk and protective factors for anxiety in pediatric epilepsy ............................ 40
Anxiety and health related quality of life in epilepsy ....................................... 53
ix
Statement of the Problem and Purpose ..................................................................... 54
Research Questions and Hypotheses ........................................................................ 55
Research question 1 ........................................................................................ 55
Research question 2 ........................................................................................ 57
Research question 3 ........................................................................................ 58
Research question 4 ........................................................................................ 61
Hypothesized model ....................................................................................... 62
Chapter 3: Methods ....................................................................................................... 65
Participants .............................................................................................................. 65
Procedures ............................................................................................................... 65
Measures ................................................................................................................. 66
Demographic information ............................................................................... 66
Seizure information ........................................................................................ 66
Parent history of psychopathology .................................................................. 66
Anxiety ........................................................................................................... 67
Stigma ............................................................................................................ 68
Illness cognitions ............................................................................................ 69
Quality of life ................................................................................................. 70
Cognitive functioning ..................................................................................... 72
Analyses .................................................................................................................. 74
Preliminary analyses ....................................................................................... 74
Analysis of the research questions................................................................... 74
x
Chapter 4: Results ......................................................................................................... 78
Preliminary Data Analysis ....................................................................................... 78
Descriptive statistics ....................................................................................... 78
Assumptions ................................................................................................... 83
Main Analyses ......................................................................................................... 83
Research question 1 ........................................................................................ 83
Research question 2 ........................................................................................ 86
Research question 3 ........................................................................................ 88
Research question 4 ........................................................................................ 91
Summary ........................................................................................................ 95
Chapter 5: Discussion .................................................................................................... 97
Summary ................................................................................................................. 97
Anxiety ........................................................................................................... 97
Parent history of psychopathology .................................................................. 98
Parent perceptions of stigma ........................................................................... 98
Parent illness cognitions ............................................................................... 101
Seizure severity ............................................................................................ 102
Quality of life ............................................................................................... 105
Limitations ............................................................................................................ 107
Recommendations for research .............................................................................. 109
Implications for clinical practice ............................................................................ 111
Conclusion ............................................................................................................ 112
References................................................................................................................... 114
xi
List of Tables
Table 1: Demographic characteristics...................................................................... 79
Table 2: Epilepsy characteristics ............................................................................. 80
Table 3: Parent reported questionnaires ................................................................... 81
Table 4: Correlation matrix ..................................................................................... 82
Table 5: Parent history of psychopathology regression model ................................. 84
Table 6: Stigma regression model ........................................................................... 85
Table 7: Illness cognitions regression model ........................................................... 86
Table 8: Stigma mediation model............................................................................ 87
Table 9: Illness cognitions mediation model. .......................................................... 87
Table 10: Effect of parent history on stigma at varying levels of seizure severity ...... 88
Table 11: Effect of parent history on illness cognitions at varying levels of seizure
severity ..................................................................................................... 89
Table 12: Effect of stigma on anxiety at varying levels of seizure severity ................ 90
Table 13: Health-related quality of life regression model .......................................... 92
Table 14: Health-related quality of life cognitive domain regression model .............. 93
Table 15: Health-related quality of life emotional domain regression model ............. 94
Table 16: Health-related quality of life social domain regression model .................... 94
Table 17: Health-related quality of life physical domain regression model ................ 95
Table 18: Summary of quality of life findings by domain.......................................... 96
xii
List of Figures
Figure 1: Classification of epilepsy ............................................................................ 9
Figure 2: Classification of seizure type ..................................................................... 11
Figure 3: Hypothesized moderation on parent perceptions of stigma ........................ 60
Figure 4: Hypothesized moderation on parent illness cognitions ............................... 61
Figure 5: Hypothesized model including parent perceptions of stigma...................... 63
Figure 6: Hypothesized model including parent illness cognitions ............................ 63
Figure 7: Effect of stigma on anxiety at varying levels of seizure severity ................ 91
1
Chapter 1: Introduction
Epilepsy is a neurological disorder characterized by a predisposition to generate
seizures (Fisher et al., 2014). Approximately 1% of children are diagnosed with epilepsy,
making it the most common chronic neurologic condition in childhood (Aaberg et al., 2017;
P. R. Camfield & Camfield, 2015; Russ et al., 2012). Epilepsy places a considerable burden
on society and in the United States the economic burden of epilepsy is estimated to be 9.6
to 12.5 billion dollars annually (Begley et al., 2000; Institute of Medicine, 2012; Yoon,
Frick, Carr, & Austin, 2009). The etiology of epilepsy is diverse and includes structural,
genetic, infectious, metabolic, immune, and unknown causes. While seizures are the
defining feature of epilepsy, the cognitive, social, and emotional burden that can be
associated with the underlying brain dysfunction can have a significant impact on quality
of life in youth with epilepsy (Fisher et al., 2014).
Epilepsy is considered a disease of brain networks, wherein seizures are just one
symptom of brain dysfunction (Smith, 2016). Youth with epilepsy are at increased risk for
cognitive difficulties because of underlying brain dysfunction and due to the effects of
seizures and AEDs on developing brains (Institute of Medicine, 2012). There is a greater
risk for negative psychosocial outcomes in epilepsy, such as lower social competence,
more school problems, and limited activity when compared to healthy children (Russ et al.,
2012). Epilepsy affects social functioning by limiting an individual’s participation in
activities and restricting their independence (Institute of Medicine, 2012).
2
When compared to healthy children or youth with other chronic health conditions,
youth with epilepsy are at an increased risk for a variety of psychopathologies, including
anxiety, depression, attention-deficit/hyperactivity disorder, and autism (Austin et al.,
2011; Caplan et al., 2005; Dunn, Austin, & Perkins, 2009; Reilly, Kent, & Neville, 2013).
Seizure related variables (e.g., high seizure frequency, poor seizure control, and multiple
anti-epileptic medications [AEDs]) and psychosocial factors (e.g., stigma, coping, and
family functioning) are implicated in the increased risk of psychopathology in youth with
epilepsy (Caplan et al., 2004; Dunn & Austin, 2004; Reilly et al., 2013).
Youth with epilepsy are at a markedly increased risk for developing anxiety when
compared to healthy controls (Alwash, Hussein, & Matloub, 2000; Jones et al., 2007; Russ
et al., 2012) and when compared to youth with other chronic health conditions (Pinquart &
Shen, 2011). However, despite its prevalence, anxiety has been referred to as the
“forgotten” disorder in epilepsy because it has been widely ignored in the epilepsy
literature (Gandy et al., 2015). The etiology of anxiety in pediatric epilepsy appears to be
multifactorial and likely involves a variety of biological, psychosocial, and familial risk
and protective factors (Jones et al., 2015).
There is emerging evidence that anxiety and epilepsy have a bidirectional
relationship, as features of anxiety occasionally precede the onset of seizures, suggesting a
common underlying biological vulnerability (Adelöw, Andersson, Ahlbom, & Tomson,
2012; Jones et al., 2007; Kanner, 2009). Higher symptoms of anxiety in youth with
epilepsy may be related to dysfunction within the limbic system and/or neurotransmitter
3
pathways that create vulnerabilities to internalizing psychopathology. Higher symptoms of
anxiety in youth with epilepsy may also be attributable to seizure-related variables, such as
taking more than one AED (i.e., polytherapy), high seizure frequency, or poor seizure
control (Reilly et al., 2013).
There are also a variety of psychosocial variables that are unique to youth with
epilepsy that make them more vulnerable to anxiety. Children with epilepsy are often
confronted with the unpredictable nature of seizures, which while anxiety provoking on its
own, can be compounded by reduced control of the environment and parental
overprotectiveness (Pinquart & Shen, 2011). Youth with epilepsy may also experience
social anxiety because of the increased risk for peer rejection and victimization and the
social stigma of epilepsy (Davies, Heyman, & Goodman, 2003; Pinquart & Shen, 2011).
These psychosocial complications create a difficult social and family environment that
includes elevated stress, restriction of activities, and isolation (Ellis, Upton, & Thompson,
2000).
Parents have become a significant focus of research examining the environmental
risk and protective factors for anxiety in healthy children (Creswell et al., 2011; Gregory
& Eley, 2007), and this is an area of budding research in youth with epilepsy as well (Jones
& Reilly, 2016; Rodenburg, Meijer, Dekovic, & Aldenkamp, 2006; Schraegle & Titus,
2017a). Recent research has demonstrated that parent history of psychopathology is related
to anxiety in youth with epilepsy (Adewuya & Ola, 2005; Jones & Reilly, 2016; Schraegle
& Titus, 2017a), and parent rejection is related to more internalizing problems (Rodenburg
4
et al., 2006). Conversely, positive parent-child relationships have been found to be related
to lower internalizing symptoms (Rodenburg et al., 2006). Research regarding parent
factors that influence anxiety in youth with epilepsy is emerging but remains limited, and
significant work is needed to match the understanding of factors that impact the
development of anxiety in children (Murray, Creswell, & Cooper, 2009).
Anxiety has important implications for the quality of life in youth with epilepsy. In
the general population, individuals with anxiety report lower quality of life, and successful
treatment of anxiety is associated with improvements in quality of life (Hofmann, Wu, &
Boettcher, 2014; Olatunji, Cisler, & Tolin, 2007). Research in youth with epilepsy suggests
that internalizing symptoms have a more negative impact on quality of life than other
demographic or epilepsy-related variables (Stevanovic, Jancic, & Lakic, 2011). However,
more research is needed to elucidate the medical and psychosocial risk factors of anxiety
to improve quality of life in youth with epilepsy (Scott, Sharpe, Hunt, & Gandy, 2017).
A recent International League Against Epilepsy Task Force report (Dunn et al.,
2016) suggested that it is important to assess for reversible causes of anxiety in patients
with epilepsy, and Ekinci et al. (2009) emphasized the importance of investigating family
factors to identify opportunities for intervention and successful treatment that can improve
health-related quality of life. Research grounded in theory is needed to provide greater
insight into the risk and protective factors for anxiety, and while individuals with epilepsy
experience high levels of stigma, research examining the relationship between stigma and
anxiety in youth with epilepsy is severely limited. Additionally, parents provide a unique
5
and important context for the development of anxiety, and to date, no research has
examined how parent illness cognitions may impact anxiety in youth with epilepsy.
Similarly, while parental psychopathology is a known risk factor for anxiety in the general
population, research on the genetic and environmental influences of anxiety in youth with
epilepsy is sparse.
The proposed research study aims to examine the medical and psychosocial risk
factors for anxiety in youth with epilepsy. Participants included children and adolescents
with epilepsy at a tertiary outpatient clinic in Central Texas who were referred by their
neurologists for a neuropsychological evaluation to assist with treatment planning. Parent
perceptions of stigma and parent illness cognitions were examined to determine their
relationship with parent reported features of anxiety, seizure-related variables, and parent
history of psychopathology. Finally, this research reviews the impact of parent reported
anxiety on health-related quality of life in youth with epilepsy.
6
Chapter 2: Literature Review
This chapter will provide an overview of epilepsy, anxiety, and the current
understanding of anxiety within pediatric epilepsy. It will begin with a description of
epilepsy and its prevalence in youth and provide a brief overview of the etiology,
classification, and treatment of epilepsy and will conclude with outcomes in pediatric
epilepsy. Next, this review will provide a description of anxiety and its prevalence in youth,
with an overview of the etiology of anxiety, associated risk and protective factors,
treatment options, and outcomes for youth with anxiety. Finally, this review will describe
the literature that examines the relationship between anxiety and epilepsy and the
prevalence of anxiety symptoms in individuals with epilepsy. Various biological and
environmental factors that place youth with epilepsy at greater risk for anxiety will be
considered, along with a discussion of gaps in our understanding of anxiety within pediatric
epilepsy. The chapter will conclude with the research questions and hypotheses related to
how parent factors influence anxiety in youth with epilepsy.
Epilepsy
Epilepsy is a neurological condition characterized by the occurrence of
unpredictable seizures (Institute of Medicine, 2012). An epileptic seizure is caused by
neuronal activity in the brain that is abnormal and excessive; it is characterized by variable
signs or symptoms dependent on the location of the neuronal activity (Fisher et al., 2014).
It is important to note the distinction between epilepsy and seizures; seizures are the event,
7
while epilepsy is the disease associated with spontaneous and recurring seizures (Fisher et
al., 2014). The Institute of Medicine (2012) considers epilepsy a spectrum of disorders that
can vary in severity, type, and impact on individuals affected.
Incidence, prevalence, cost, and burden of pediatric epilepsy. Epilepsy is the
most common chronic neurologic condition in childhood, affecting approximately 1% of
children (Aaberg et al., 2017; P. R. Camfield & Camfield, 2015; Russ et al., 2012). An
estimated 6.8 million people have been diagnosed with epilepsy and 5.7 million people
have active epilepsy in developed countries (Ngugi, Bottomley, Kleinschmidt, Sander, &
Newton, 2010). According to a recent Norwegian study, in the first ten years of life,
approximately 1 out of every 150 children will be diagnosed with epilepsy (Aaberg et al.,
2017). Incidence rates in children range from 41-187/100,000 (C. S. Camfield, Camfield,
Gordon, Wirrell, & Dooley, 1996; P. R. Camfield & Camfield, 2015; Mung’ala-Odera et
al., 2008). There is a higher incidence of epilepsy in the first year of life and in rural and
underdeveloped countries (P. R. Camfield & Camfield, 2015). Researchers suggest that the
incidence of epilepsy is declining in countries with higher incomes due to the reduced risk
of infection and traumatic brain injury that cause epilepsy (Aaberg et al., 2017). The
prevalence of epilepsy ranges from 3.2-6.7/1,000 children with a median prevalence of
active pediatric epilepsy of 4.7/1,000 (P. R. Camfield & Camfield, 2015; Ngugi et al.,
2010). The economic burden of epilepsy is estimated to be 9.6 to 12.5 billion dollars
annually in the United States; this includes direct costs of hospitalizations and indirect costs
of lost productivity (Begley et al., 2000; Institute of Medicine, 2012; Yoon et al., 2009).
8
Etiology. The etiology of epilepsy is diverse and includes structural, genetic,
infectious, metabolic, immune, and unknown etiologies. Structural abnormalities of the
brain that are visible on neuroimaging (e.g., lesions) may cause seizures, and typical causes
of structural abnormalities include stroke, traumatic brain injury, infections, and
malformations of cortical development (Scheffer et al., 2017). Infections (e.g., meningitis,
encephalitis) are common and preventable risk factors for epilepsy (Vezzani et al., 2016).
Certain genetic mutations (known or presumed), an array of metabolic disorders, and
immune disorders may also cause epilepsy (Scheffer et al., 2017). While there are a
multitude of etiologies of epilepsy, the cause of epilepsy is unknown in about 50% of
children (P. R. Camfield & Camfield, 2015). An individual’s epilepsy can have multiple
etiologies, and each etiology has implications for treatment (Scheffer et al., 2017).
Diagnosis. According to the ILAE, epilepsy is diagnosed in one of three ways: (a)
two or more unprovoked seizures that occur more than a day apart; (b) one unprovoked
seizure with >60% probability of another seizure occurring in the next ten years; or (c)
diagnosis of an epilepsy syndrome (Fisher et al., 2014). Unprovoked seizures imply the
“absence of a temporary or reversible factor” that lowers the threshold for seizures on an
otherwise normal brain (Fisher et al, 2014). Examples of provoked seizures include
seizures associated with concussion, fever, or alcohol withdrawal (Fisher et al, 2014).
Classification. Epilepsy classification is a complex process that can be based on a
variety of factors. Clinicians classify seizures by finding familiar patterns in the signs and
symptoms of the seizure and utilizing ancillary data such as electroencephalograms (EEGs)
9
and magnetic resonance imaging (MRIs) (Fisher, Cross, D’Souza, et al., 2017). Due to the
lack of fundamental knowledge of seizures, it is difficult to classify seizures based on their
pathophysiology; however, seizures may be classified in many ways, such as by the
anatomic structures involved (e.g., frontal/temporal), the networks involved (e.g.,
neocortical, limbic), or the observable or treatment-related aspects of the seizures (e.g.,
behavioral semiology, EEG pattern, response to medication) (Fisher, Cross, D’Souza, et
al., 2017). The ILAE provides a framework for understanding the classification of epilepsy
by providing a multi-level classification system that involves classification of seizure type,
epilepsy type, and syndrome, as well as identification of the etiology (see Figure 1)
(Scheffer et al., 2017).
Figure 1: Classification of epilepsy. This figure illustrates the various levels of
classification of epilepsy based on the ILAE framework. This figure is
adapted from Scheffer et al. (2017).
10
The ILAE developed an operational system of classification of seizure type for use
by clinicians that classifies seizures by location of onset and the signs and symptoms of the
seizure (Fisher, Cross, D’Souza, et al., 2017). The next level of classification is for epilepsy
type, which can include multiple seizure types. Epilepsy can also be classified based on
the syndrome, which is defined as a cluster of features that occur together (Scheffer et al.,
2017). The method of seizure classification utilized is dependent on the ultimate goal of
classification. For the purposes of this dissertation, classification by seizure type and
syndrome will be defined.
Seizure Type. According to the ILAE, classification by seizure type is a “useful
grouping of seizure characteristics for purposes of communication” (Fisher, Cross, French,
et al., 2017). The first step in classification of seizure type is to define the type of seizure
onset (Fisher, Cross, D’Souza, et al., 2017). Focal and generalized seizures are the two
main types of seizure onset, but seizure onset may also be unknown (Fisher, Cross,
D’Souza, et al., 2017). Seizures are then classified based on whether they lead to a loss of
awareness. Finally, seizures are classified based on the most prominent aspect of the
seizure (Fisher, Cross, D’Souza, et al., 2017). The ILAE recommends that clinicians also
provide additional descriptors that include sensations, emotions, and cognitions
experienced during the seizure, movements of specific body parts, and laterality (Fisher,
Cross, D’Souza, et al., 2017). See Figure 2 for visual representation of the classification of
seizure types.
11
Figure 2: Classification of seizure type. This figure illustrates the most recent ILAE
guidelines for classification of seizure type. This figure is adapted from
Fisher, Cross, D’Souza, et al. (2017).
Seizures with a focal onset occur within one hemisphere; the onset can be
subcortical, localized, or widely distributed (Fisher, Cross, D’Souza, et al., 2017). Focal
seizures are then classified based on whether the individual is aware during the seizure
(Fisher, Cross, D’Souza, et al., 2017). Focal seizures can be further characterized by the
“first prominent sign or symptom” of the seizure, which can be motor (e.g., jerking, loss
of muscle tone) or nonmotor (e.g., hallucination) (Fisher, Cross, D’Souza, et al., 2017).
12
Generalized seizures originate in a network of neurons that span bilaterally
(Institute of Medicine, 2012). Generalized seizures are further characterized based on
whether they are motor or nonmotor. Nonmotor generalized seizures are also known as
absence seizures, which “present with a sudden cessation of activity and awareness”
(Fisher, Cross, D’Souza, et al., 2017).
Syndromes. An epilepsy syndrome is “a complex of clinical features, signs, and
symptoms that together define a distinctive, recognizable clinical disorder” (Berg et al.,
2010). Epilepsy syndromes are characterized by typical age of onset, EEG findings, seizure
types, and imaging features (Institute of Medicine, 2012; Scheffer et al., 2017).
Classification by epilepsy syndrome provides information for medical treatment planning
as well as prognosis.
Treatment of epilepsy. A variety of treatments and therapies are available to treat
epilepsy, including medication, vagus nerve stimulation, surgery, and diet.
Medication. Anti-epileptic drugs (AEDs) are the initial treatment of choice for
children with epilepsy; AEDs work through a variety of mechanisms (e.g., enhancing
inhibitory neurotransmission or suppressing neuronal excitability) to prevent epileptic
seizures (Ortinski & Meador, 2004; Schmitz, 2002). If a child is taking one medication it
is considered monotherapy; approximately 46-61% of children achieve seizure freedom
after receiving the appropriate medication (Arts et al., 2004; C. S. Camfield, Camfield,
Gordon, & Dooley, 1997). Polytherapy, which is the use of more than one AED, may be
needed to achieve seizure freedom, but is associated a higher risk of side effects (Bergin,
13
2003). Approximately 42% of children who receive a second AED achieve seizure freedom
(Arts et al., 2004; C. S. Camfield et al., 1997). Generally, children remain on medication
for two years, with a gradual withdrawal of medication; 70% of children remain seizure-
free after medication withdrawal (Bergin, 2003).
When an individual’s seizures cannot be controlled with medication, the epilepsy
is defined as intractable (also described as refractory, drug resistant, or pharmacoresistant)
(Kwan et al., 2010). An ILAE task force defined intractable epilepsy across two levels.
Level 1 criteria determine whether the intervention leads to seizure freedom as well as
whether there are adverse effects of the treatment (Kwan et al., 2010). The Level 2
definition of intractable epilepsy is “failure of adequate trials of two tolerated and
appropriately chosen and used AED schedules (whether as monotherapies or in
combination) to achieve seizure freedom” (Kwan et al., 2010). A number of definitions
have been applied to the term intractable epilepsy, leading to variable criteria and different
results, but approximately 6-10% of children have intractable epilepsy (Arts et al., 2004;
Berg et al., 2001). When AED therapy is ineffective, neurologists will consider adjunctive
therapies, such as vagus nerve stimulation (Schmitz, 2002).
Vagus nerve stimulation. Vagus nerve stimulation (VNS) is a treatment that uses
an implanted device to send electrical signals to the brain through the vagus nerve and can
be used in individuals over the age of twelve (Andrews, 2010). VNS can reduce the
frequency of seizures by about 50% in individuals with intractable epilepsy who are not
surgical candidates (Morris et al., 2013). In a study of 347 children, approximately 43% of
14
children with a VNS had a reduction in seizures by over 50% and 6.7% were seizure free
after two years with the implant (Orosz et al., 2014).
Surgery. Seizure control can also be achieved through surgical removal of
epileptogenic brain tissue (Schmitz, 2002). Surgical intervention is generally considered
after three years of intractable epilepsy and if the patient is a good surgical candidate (e.g.,
localized structural lesion) (Schmitz, 2002). According to a meta-analysis, approximately
27-66% of patients achieve seizure freedom after epilepsy surgery (Téllez-Zenteno, Dhar,
& Wiebe, 2005).
Other treatments. Other treatment options for epilepsy include diet and behavioral
treatment. The ketogenic diet is a high fat, low carbohydrate diet that has been effective in
the treatment of certain epilepsy syndromes and conditions (Kossoff et al., 2009). The
modified Atkins diet and the low glycemic index treatment are other dietary therapies that
may also be useful in the treatment of intractable epilepsy (Kossoff et al., 2009). Behavioral
strategies, such as relaxation, biofeedback, and self-control, have been described in the
literature, but are poorly researched and limited in their effectiveness (Schmitz, 2002).
While there are a variety of efficacious treatments for seizures, it is important to note that
seizures are just one aspect of epilepsy.
Outcomes and quality of life in epilepsy. The ILAE Task Force conceptualizes
epilepsy as “a disorder of the brain characterized by an enduring predisposition to generate
epileptic seizures, and by the neurobiologic, cognitive, and social consequences of this
condition” (Fisher et al., 2014). Seizure freedom, while important, does not necessarily
15
translate to improved quality of life. Epilepsy also impacts cognition, academic
functioning, psychosocial functioning, and emotional functioning. “If epilepsy is a disease
of brain networks and cognition and behavior are the primary functions of those networks,
then epilepsy may be as much a disorder of cognition and behavior as it is of seizures, with
cognitive and behavioral symptoms either predating seizures, or vice versa” (Smith, 2016).
It is important to consider that cognitive, academic, psychosocial, behavioral, and
emotional difficulties associated with epilepsy may be aspects of the epilepsy itself, rather
than just comorbidities.
Cognitive functioning. Seizures, as well as medications for seizures, affect
cognitive ability in individuals with epilepsy. Antiepileptic drugs change neuronal activity
and can lead to cognitive side effects, particularly in individuals on polytherapy (Ortinski
& Meador, 2004). Common side effects of AEDs include sedation, dizziness, and
distractibility (Ortinski & Meador, 2004). AEDs also impact neurodevelopment; therefore
children are at an increased risk for cognitive side effects of these medications (Bergin,
2003; Ortinski & Meador, 2004; Reuner, Kadish, Doering, Balke, & Schubert-Bast, 2016).
Epilepsy itself is also a risk factor for cognitive difficulties. In a meta-analysis of
cognitive functioning in idiopathic generalized epilepsy (IGE), researchers found that
individuals with IGE had significantly lower scores across all cognitive domains, except
for visual-spatial abilities, when compared to healthy controls (Loughman, Bowden, &
D’Souza, 2014). Loughman and colleagues (2014) also found that approximately 25% of
individuals with IGE had an intellectual disability or borderline cognitive difficulties.
16
Children with epilepsy are at considerable risk for cognitive difficulties because
their brains are still developing (Institute of Medicine, 2012). Reuner et al. (2016) found
that children with new-onset epilepsy had impaired cognitive performance compared to
healthy controls, even before starting medication therapy. Furthermore, they found that
children with chronic epilepsy had even poorer cognitive performance than children with
new onset epilepsy. Several seizure and brain-related factors, such as earlier onset of
seizures, cerebral lesions, and seizure severity, frequency, type, and duration are related to
cognitive functioning in individuals with epilepsy (Ortinski & Meador, 2004). Seizure
control and cognitive functioning are important outcomes to consider because chronic
intractable epilepsy and low intelligence are risk factors for poor psychosocial functioning
in individuals with epilepsy (Geerlings et al., 2015).
Psychosocial functioning. Children with epilepsy are at greater risk for negative
psychosocial outcomes compared to children without seizures. Epilepsy may affect the
ability to function independently and participate in social activities (Institute of Medicine,
2012). Adolescents may be particularly affected because epilepsy is associated with a loss
of independence and individuals with epilepsy are unable to drive. In a report from the
National Survey of Children’s Health, researchers found that children with epilepsy were
more likely to have low social competence, school problems, and limited activity when
compared to children who were not diagnosed with epilepsy (Russ et al., 2012). Epilepsy
also has psychosocial consequences that extend into adulthood. In a study of adults with
epilepsy in the Netherlands, researchers found that having epilepsy affects employment,
17
marital status, learning achievement, and independence (Shackleton, Kasteleijn-Nolst
Trenite, de Craen, Vandenbroucke, & Westendorp, 2003). Individuals with epilepsy might
also experience difficulty with interpersonal relationships due to their experiences of
perceived stigma (McCagh, Fisk, & Baker, 2009).
Epilepsy can cause psychosocial difficulties for the whole family of an individual
with epilepsy; this includes stress, restriction of activities, and stigmatization (Ellis et al.,
2000). In a study of 138 young adults with epilepsy, researchers found that poor family
support was a strong predictor of poor psychosocial outcomes (Geerlings et al., 2015). It is
important to understand and address family and psychosocial functioning to improve
quality of life in individuals with epilepsy.
Stigma. Individuals with epilepsy are at an increased risk of feeling stigmatized and
discriminated against because of their epilepsy (Baker, Brooks, Buck, & Jacoby, 2000).
Stigma is the experience of feeling discredited because an individual is different or
undesirable to others in society (Goffman, 1968). Stigma can be experienced internally
(e.g., feelings, thoughts, and beliefs about the self), interpersonally (e.g., interactions with
others), and institutionally (e.g., differential treatment in society) (Muhlbauer, 2002).
Health-related stigma can be defined as “a social process or related personal experience
characterized by exclusion, rejection, blame, or devaluation that results from experience or
reasonable anticipation of an adverse social judgment about a person or group identified
with a particular health problem” (Weiss & Ramakrishna, 2006). Theoretical models of
stigma suggest six dimensions of stigma: concealability (e.g., visibility), course of the mark
18
(e.g., salience over time), disruptiveness, aesthetics (e.g., unattractiveness), origin
(congenital, accidental, or intentional), and peril (e.g., danger to others) (E. E. Jones, 1984).
Youth with epilepsy are particularly vulnerable to internalized perceptions of stigma. In a
study of 174 youth with epilepsy, researchers found that child perceptions of stigma were
related to greater need for information and support, greater child fear and worry about
seizures, more severe seizures, and younger age (Austin, Perkins, & Dunn, 2014).
Psychopathology. Youth with epilepsy are at increased risk for anxiety, depression,
attention-deficit/hyperactivity disorder, and autism when compared to healthy controls and
other youth with chronic illness (Austin et al., 2011; Caplan et al., 2005; Dunn et al., 2009;
Reilly et al., 2013). In a large population-based study, neurodevelopmental spectrum
disorders, including developmental delays, language problems, dyslexia, learning
disorders, and autism spectrum disorder were found in 41.7% of children with epilepsy
(Berg, Caplan, & Hesdorffer, 2011). In another population-based study, 21% of children
with epilepsy met criteria for autism (Reilly et al., 2014). Reilly and colleagues (2014)
found that 33% of children with epilepsy met criteria for ADHD. Children with epilepsy
are also reported to have more behavior problems than their siblings (11.3% compared to
4.6%) (Austin et al., 2011).
Rates of anxiety and depression are also elevated in children with epilepsy, with
prevalence in population-based studies ranging from 5% to 24% in anxiety and 7% to
13.4% in depression (Berg et al., 2011; McDermott, Mani, & Krishnawami, 1995; Reilly
et al., 2014). In a meta-analysis, researchers found large effect sizes (d=1.27) for parent
19
reported internalizing problems when comparing children with epilepsy and normative
controls (Rodenburg, Stams, Meijer, Aldenkamp, & Dekovic, 2005). In a population study
of over 10,000 children, which included 67 children with epilepsy and 47 children with
diabetes, researchers found that the rate of “emotional” psychiatric disorders in individuals
with epilepsy was about 16%, compared to 6.4% in children with diabetes and 4.2% in the
control group (Davies et al., 2003).
A bidirectional relationship may exist between mood/anxiety disorders and
epilepsy (Kanner, 2009). Jones et al. (2007) found that forty-five percent of children with
idiopathic epilepsy had an onset of a psychiatric disorder prior to their first seizure.
Additionally, the higher prevalence of psychopathology and cognitive and linguistic
impairments in children with epilepsy suggests that there is a common underlying
neuropathology (Austin & Caplan, 2007). Berg and colleagues (2011) demonstrated that
individuals with “complicated” epilepsy have more neurodevelopmental and psychiatric
disorders than those with uncomplicated epilepsy. High seizure frequency, poor seizure
control, and polytherapy are all associated with greater risk for psychopathology in
pediatric epilepsy (Reilly et al., 2013). Other seizure variables, including seizure type, age
of onset, and duration, are not consistently associated with psychopathology (Reilly et al.,
2013). While factors related to epilepsy are associated with higher levels of psychiatric
problems in children and adolescents with epilepsy, psychosocial factors may also affect
psychopathology in children with epilepsy (Caplan et al., 2004; Dunn & Austin, 2004).
Despite the high prevalence of psychiatric symptoms in pediatric epilepsy only one third
20
of youth with epilepsy and mental health conditions are diagnosed (Reilly et al., 2014), and
only 33% of youth with epilepsy with affective and anxiety disorders actually receive
mental health treatment (Caplan et al., 2005).
Quality of life. While seizure control is important, the focus of research in epilepsy
has shifted to consider implications for quality of life. Quality of life is an “individuals’
perceptions of their position in life in the context of the culture and value systems in which
they live and in relation to their goals, expectations, standards, and concerns” (“WHO |
WHOQOL,” n.d.). In a study that examined the trajectories of health-related quality of life
in 120 children with newly diagnosed epilepsy, Loiselle and colleagues (2016) found that
42% of children were at risk for low quality of life. Several variables have been associated
with quality of life in youth with epilepsy, including seizure related variables (number of
AEDs, AED side effects, seizure frequency), cognitive impairment, internalizing
symptoms, socioeconomic status, and family functioning (Conway et al., 2016; Loiselle,
Ramsey, Rausch, & Modi, 2016; Reilly, Atkinson, Das, et al., 2015b).
Anxiety
Anxiety is the most common mental health disorder that affects children and
adolescents (Rockhill et al., 2010). Anxiety is the emotional reaction precipitating from the
anticipation of a real or imagined threat to the self or others (Fonseca & Perrin, 2011). It is
a “future-oriented emotion, characterized by perceptions of uncontrollability and
unpredictability over potentially aversive events and a rapid shift in attention to the focus
of potentially dangerous events or one’s own affective response to these events” (Barlow,
21
2002). While fear and anxiety of certain situations are normative and developmentally
appropriate, anxiety disorders are characterized by fear that is excessive or persistent
beyond a developmentally appropriate time period (American Psychiatric Association
[APA], 2013).
Lang (1968) described three main components to anxiety: a motor response, a
subjective/cognitive response, and a physiological response. The motor response is
characterized by behaviors, such as restlessness, immobility, and distress, activated to
avoid or escape the anxiety provoking stimulus (Lang, 1968). Worries and fearful
anticipation characterize the cognitive response to anxiety, while the physiological
response to anxiety consists of the somatic symptoms associated with high autonomic
arousal, such as increased heart rate and sweating (Lang, 1968).
The Diagnostic and Statistical Manual of Mental Disorders (DSM-V) reflects this
three-part model of anxiety in its definitions of the various anxiety disorders (American
Psychiatric Association [APA], 2013). There are several different types of anxiety
disorders that can be distinguished from each other by the cognitive ideations (thoughts
and beliefs) as well as the situations or objects that are feared or avoided (APA, 2013).
Children with separation anxiety have fears or worries that something harmful will happen
to attachment figures or something will happen that will separate them from an attachment
figure (APA, 2013). Youth with separation anxiety are typically “clingy” and may cry or
become upset when separated from an attachment figure, be reluctant or refuse to go to
school, be afraid to be alone, have stomach aches or other physical symptoms when
22
separated from attachment figures, or have nightmares about separation (Vasey, Bosmans,
& Ollendick, 2014). Children with selective mutism may have a fear of and avoid speaking
in certain situations where it is expected (e.g., in school), but are capable of talking in other
situations (e.g., around family) (APA, 2013). Specific phobias are characterized by fear of
certain, specific things, such as animals, blood, or other things in the environment. Children
with specific phobias may cry, freeze up, or cling to an attachment figure when near these
feared objects or situations (APA, 2013). Individuals with social anxiety have a fear of
embarrassing themselves or being judged by others and avoid social interactions and social
situations (APA, 2013). Panic disorder is characterized by a worry about having panic
attacks, which consist of feelings of intense fear or discomfort that are associated with
somatic symptoms and catastrophic thoughts (APA, 2013; Vasey et al., 2014).
Agoraphobia is defined as a fear of the inability to escape from certain public
environments, such as in a crowd (APA, 2013). Individuals with generalized anxiety have
persistent, excessive, and uncontrollable worry about many different types of things, such
as performance or perfectionism, and they typically have physical symptoms that
accompany this worry such as restlessness, muscle tension, concentration problems, and
difficulty sleeping (APA, 2013; Vasey et al., 2014).
Childhood through adolescence is considered a key risk period for the first
symptoms of anxiety (Beesdo-Baum & Knappe, 2012). During development, many
different types of fears and anxieties are typical and it can be challenging to distinguish
between normative fears, mild symptoms of fear and anxiety, and anxiety disorders
23
(Beesdo-Baum & Knappe, 2012). The fears of children evolve as they develop; typical
fears of early childhood are characterized by concrete and immediate threats and, as
children get older, fears evolve to anticipatory and more abstract or imagined fears
(Beesdo-Baum & Knappe, 2012). An anxiety disorder may develop when anxiety
symptoms persist, are more intense than expected for a child’s development or out of
proportion from the threat posed, and cause impairments in important areas functioning,
such as school or social functioning (Craske & Stein, 2016).
Prevalence. Anxiety is the most prevalent mental health disorder and affects one
in nine people worldwide (Craske & Stein, 2016). Estimates of the prevalence of anxiety
in children vary due to multiple factors, including age groups included, assessment
instruments, informant, and diagnostic categories used (Beesdo-Baum & Knappe, 2012).
Despite this difficulty, a recent meta-analysis estimates a world-wide prevalence rate of
anxiety in children and adolescents of 6.5%, affecting approximately 117 million youth
(Polanczyk, Salum, Sugaya, Caye, & Rohde, 2015). Prevalence rates in an additional meta-
analysis suggests a prevalence of 10.2% (Costello, Egger, & Angold, 2005). Lifetime
prevalence rates of anxiety are as high as 31.9% (Merikangas et al., 2010). The economic
burden of anxiety was estimated to be approximately $43 billion annually in the United
States in the 1990s; this includes costs associated with treatment, loss of productivity, and
mortality (Greenberg et al., 1999).
Diagnosis. Anxiety is typically diagnosed in children through diagnostic interviews
and rating scales. Semi-structured interviews utilize criteria from diagnostic systems, such
24
as the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), to determine
whether children meet certain criteria for a diagnosis. Semi-structured interviews provide
in-depth insight regarding the specific types of anxiety the child is experiencing and are
helpful with treatment planning. Clinical judgment is needed to determine the interference
of the anxiety, which consists of determining the severity, frequency, persistence, and
impairment of functioning (Craske & Stein, 2016). Diagnostic interviews can be time
consuming and difficult to use to identify children at risk for anxiety. Furthermore, while
diagnostic criteria are useful for clinicians working to treat anxiety in youth, Craske and
Stein (2016) emphasize that anxiety is a dimensional construct.
Rating scales can be administered to different informants (such as parents, teachers,
or the child) to quantify the amount, degree, or magnitude of anxiety symptoms (Silverman
& Ollendick, 2005). Rating scales are useful in assessing and screening for anxiety in youth
and are frequently utilized in research to identify and quantify features of anxiety
(Silverman & Ollendick, 2005). Such scales are especially useful to identify maintaining
variables for anxiety, as well as mediators and moderators for features of anxiety
(Silverman & Ollendick, 2005). Despite the ease of use and utility of rating scales, social-
desirability may lead to under-reporting of anxiety-symptoms on self-reported rating scales
(Silverman & Ollendick, 2005). Additionally, it is important to note that rating scales
represent a somewhat arbitrary metric, and could lead to false positives and/or false
negatives (Silverman & Ollendick, 2005). Despite some of these challenges regarding the
use of rating scales, Silverman and Ollendick (2005) suggest that measurement of anxiety
25
symptoms along a continuum allows researchers to identify degrees of disturbance and
patterns of manifestations without categorizing children or presuming an underlying
disease.
Risk and protective factors. Risk factors are defined as variables that influence,
intensify, precipitate, maintain, or predispose to maladaptation or psychopathology (Vasey
& Dadds, 2000). Complementary to this concept, protective factors “serve to protect
against the development of childhood anxiety disorders or to foster a return to a normal
developmental pathway subsequent to their onset” (p. 7, Vasey & Dadds, 2000). It is
important to note that risk and protective factors can be enduring or transient, they are not
merely additive but influence each other, and they may contribute to other
psychopathologies. Vasey and Dadds (2000) outline a variety of predisposing factors that
influence anxiety, including: genetics, neurobiology, temperament, emotion regulation,
cognitive biases and distortions, parental responses, experiences with conditioned stimuli,
and level of exposure to stimuli. Below is a brief summary of the various risk and protective
factors that serve to maintain or ameliorate symptoms of anxiety.
Genetic influences. A genetic predisposition for anxiety is clear throughout the
literature. Children of parents with anxiety are almost four times more likely to have
anxiety than children of parents without anxiety (Micco et al., 2009). The genetic aspects
of anxiety are elucidated through several avenues of research, including twin studies,
association studies, linkage studies, and genome-wide association and linkage studies.
26
Several genes have been implicated in the expression of anxiety. Studies examining
epigenetics highlight the importance of environmental factors on gene expression.
Studies of monozygotic and dizygotic twins provide information about how genes
can influence anxiety because they parcel anxiety into three factors: additive genetic
influences (e.g., gene alleles), shared environmental influences (e.g., parenting), and
unshared environmental influences (Gregory & Eley, 2011). Heritability estimates for
anxiety disorders are in the range of 30-40% (Hettema, Neale, & Kendler, 2001). Genetic
influences also account for anxious behaviors, including behavioral inhibition, shyness,
emotional dysregulation, and neuroticism (Barzman, Geise, & Lin, 2015; Battaglia et al.,
2017; Bienvenu, Hettema, Neale, Prescott, & Kendler, 2007; Johnson, Carver, Joormann,
& Cuccaro, 2016).
Several genes have been implicated in the expression of anxiety, many of which
are associated with neurotransmitter systems. The serotonin transporter polymorphism (5-
HHLPR) can vary in the number of repeated sections of DNA, and both longer and shorter
alleles have been implicated in higher anxiety personality symptoms (Schinka, Busch, &
Robichaux-Keene, 2004). Anxiety is linked to DNA changes that affect catechol-O-
methyltransferase, an enzyme that is important for both serotonin and dopamine pathways,
and the GAD1 gene, which synthesizes GABA from glutamate (Hettema et al., 2006;
McGrath et al., 2004). Finally, genes for the corticotrophin-releasing hormone, which is
released during fear, is associated with behavioral inhibition (Smoller et al., 2003).
27
Epigenetic changes are the alterations made in the chemical and physical structure
of DNA induced by environmental factors (Higley, 2016). Epigenetics can elucidate how
the environment affects gene expression. For example, in a study of rats, maternal care
(e.g., licking and grooming) produces methylation of a glucocorticoid receptor promotor
in the hippocampus associated with the stress response (Champagne et al., 2006). This
provides evidence that biological changes may be induced by environmental factors. There
are many genetic influences of anxiety, but studies reviewing epigenetics and aspects of
gene expression further complicate our understanding about the heritability of anxiety and
lay the groundwork for the importance of environmental factors. It is likely that genetic
factors predispose children to a “vulnerability” for anxiety (Barlow, 2002).
Neurobiological influences. Neurobiological factors have been assessed to
understand the development of anxiety in children. Many neurobiological influences,
including brain structures, such as the amygdala, and neurotransmitter/endocrine systems
have been associated with anxiety. The amygdala has been at the forefront of research on
brain regions involved in fear and anxiety. It is an important component of the limbic
system, which is involved in processing emotional experiences (Cummins & Ninan, 2002).
Hyperactivation of the amygdala and insula was found in a meta-analysis of imaging
studies of PTSD, social anxiety, and specific phobia; this hyperactivation was also found
in healthy subjects undergoing fear conditioning (Etkin & Wager, 2007). In other fear
conditioning paradigms, expression of the fear response has been associated with the dorsal
anterior cingulate and medial prefrontal cortex (ACC/mPFC), while the inhibition or
28
extinction of these responses has been associated with the ventral ACC/mPFC (Etkin,
Egner, & Kalisch, 2011). Etkin (2012) suggests that the ACC/mPFC are dysfunctional in
individuals with anxiety.
Multiple endocrine systems and neurotransmitters have been implicated in anxiety;
the neurotransmitters and systems involved may vary based on the anxiety disorder
experienced. GABA, which is an inhibitory neurotransmitter, has been associated with
stress and anxiety (Kalueff & Nutt, 2007). Individuals with GAD have reduced GABA-A
receptor density and GABA-A agonists reduce symptoms of anxiety (Kalueff & Nutt,
2007; Martin, Ressler, Binder, & Nemeroff, 2009). Serotonin has also been implicated in
anxiety, and some studies have determined that there is decreased 5HIAA CSF
concentration in anxiety (Martin et al., 2009). The serotonin transporter is a protein that
moves serotonin from the synaptic cleft to the presynaptic neuron and higher density has
been correlated with more anxiety symptoms in GAD (Lesch et al., 1996; Martin et al.,
2009). 5HT1A has been shown to increase anxiety at hippocampal postsynaptic receptors
and decrease anxiety at dorsal raphe nucleus autoreceptors (Martin et al., 2009). Finally,
the 5HT2 neurotransmitters increase anxiety symptoms and 5HT2 antagonists reduce
anxiety symptoms (Martin et al., 2009; Vaswani, Linda, & Ramesh, 2003).
Temperament. Temperament is the socioemotional behavior seen in early
development that shapes a child’s mood and behavior in certain contexts (Pérez-Edgar &
Fox, 2005). Behavioral inhibition, negative affect, harm avoidance, and novelty seeking
are all temperaments that have been associated with symptoms of anxiety (Pérez-Edgar &
29
Fox, 2005). Temperament is thought to affect anxiety in four ways. First, in conjunction
with the diathesis-stress model, temperament may interact with environmental stressors to
predispose youth to anxiety (Vasey et al., 2014). The pathoplasticity model suggests that a
child’s temperament may also affect how parents or others interact with them, which
shapes their environment (Vasey et al., 2014). Next, changes in temperament may be a
product of the development of the anxiety disorder, which is known as the complication or
scar model (Vasey et al., 2014). Finally, the continuity model suggests that temperament
and anxiety have the same underlying processes and reflect the same construct (Vasey et
al., 2014).
Behavioral inhibition is the tendency to be shy and cautious, which is a
temperament that has been associated with anxiety (Hirshfeld et al., 1992; Kagan, Reznick,
& Snidman, 1987; Kagan & Snidman, 1999). Children with behavioral inhibition are likely
to be highly reactive to unfamiliar situations, which constrains the probability that the child
will be uninhibited in his or her behavior (Kagan & Snidman, 1999). Behaviorally inhibited
children have more physiological reactions to anxiety (e.g., increased heart rate, higher
cortisol) and are more likely to experience anxiety (Hirshfeld et al., 1992; Kagan &
Snidman, 1999). Having a behaviorally inhibited temperament is associated with
physiological aspects of anxiety and shapes avoidance behavior of anxiety provoking
environments.
Negative affect is characterized by the experience of negative emotions, high
subjective distress, and displeasurable association with the environment (Lonigan, Phillips,
30
& Hooe, 2003). Negative affect is a component of the tripartite model of anxiety and
depression, and high levels of negative affect are associated with anxiety in adolescents
(Lonigan et al., 2003). In a meta-analysis of studies examining temperament in panic
disorder, social anxiety disorder, and obsessive-compulsive disorder (OCD), researchers
found that harm avoidance was positively associated with symptoms of all three diagnoses
and there was a marginal negative relationship between novelty seeking and social anxiety
and OCD (Kampman, Viikki, Järventausta, & Leinonen, 2014). It is important to note that
while temperament has been associated with the development of anxiety, a child is both
the producer of and a product of their environment because children develop through a
reciprocal interaction with the environment (Pérez-Edgar & Fox, 2005).
Gender. Women are more likely than men to be diagnosed with an anxiety disorder;
by the age of six, girls are two times more likely to have experienced anxiety (Costello et
al., 2005; Craske & Stein, 2016; Lewinsohn, Gotlib, Lewinsohn, Seeley, & Allen, 1998).
In a large sample of adults, researchers found that not only was anxiety more prevalent in
women, but it was also more disabling and resulted in greater illness burden (McLean,
Asnaani, Litz, & Hofmann, 2011). Despite the greater prevalence of anxiety in women and
girls, it is still unclear why they are at greater risk for anxiety (Costello et al., 2005; Craske
& Stein, 2016). When adjusted for potentially cofounding factors, anxiety is still more
prevalent in girls (Lewinsohn et al., 1998).
Cognition, control, and learning. Information processing biases, composed of
attention, interpretation, and memory biases, are cognitive distortions that are associated
31
with anxiety (Muris & Field, 2008). These cognitive distortions can be explained by the
cognitive-behavioral theory of child psychopathology that suggests that anxiety results
from schemas regarding danger and vulnerability that lead children to focus on threatening
information and ultimately develop maladaptive thought patterns that maintain anxiety
(Kendall, 1985). While anxiety and cognitions are inter-related, it is important to note that
this does not necessarily imply a causal relationship; additionally, both environmental
factors, such as learning, and genetic factors play a role in the development of cognitive
distortions (Muris & Field, 2008).
Attention bias is the tendency to be hyper-attentive towards threatening information
and is generally measured through Stroop tasks with emotionally laden words and dot-
probe tasks (Muris & Field, 2008). A meta-analysis concluded that anxious children and
adults demonstrate threat-related biases when compared to healthy controls (Bar-Haim,
Lamy, Pergamin, Bakermans-Kranenburg, & van IJzendoorn, 2007). Youth with anxiety
consistently demonstrate interpretation bias, which is the tendency to perceive ambiguous
situations as threatening (Miers, Blöte, Bögels, & Westenberg, 2008; Muris & Field, 2008;
Rozenman, Amir, & Weersing, 2014). Finally, a tendency to recall memories congruent
with anxious cognitions is considered memory bias; however, evidence for this type of bias
is lacking in studies of youth and adults with anxiety (Muris & Field, 2008). While there
is evidence that children and adolescents demonstrate information processing biases, it is
important to consider that developmental level will affect a child’s ability to demonstrate
32
and verbalize cognitive distortions (Cartwright-Hatton, Reynolds, & Wilson, 2011; Muris
& Field, 2008).
Researchers suggest that experience with uncontrollable events may predispose a
child to a psychological vulnerability that leads them to perceive events as outside of their
control (Chorpita & Barlow, 1998). Chorpita and Barlow (1998) propose that in early
development, such uncontrollable events lead to a psychological vulnerability that is a
mediator to anxiety, while later in development, the psychological vulnerability amplifies
anxiety and acts as a moderator. In a recent meta-analysis, researchers found a mean effect
size of -.524 between perceived control and anxiety; this relationship was stronger in adults
than children (Gallagher, Bentley, & Barlow, 2014).
Learning also plays a key role in the development of anxiety. Rachman (1977,
1991) proposed three pathways for the acquisition of fear: conditioning, modeling or
vicarious learning, and verbal acquisition. In other words, children may acquire fear
through direct experiences, through observation of the reactions of others, through verbal
information, or through a combination of all three (Field & Purkis, 2011).
Family factors. Environmental factors play an important role in the development
of anxiety, and parents have become a large focus of research examining environmental
risk and protective factors for anxiety (Creswell et al., 2011; Gregory & Eley, 2007).
Murray et al. (2009) describes three pathways in which parents can influence the
development of anxiety. First, parents may socialize their child in a way that leads the child
to perceive that they are unable to cope with the dangers of the world (Murray et al., 2009).
33
Next, a child may learn anxiety from an anxious parent who models or verbally mediates
anxiety (Murray et al., 2009). Finally, Murray and colleagues (2009) suggest that parents
may respond to a child’s anxiety in ways that maintain or intensify anxiety (e.g.,
accommodation and avoidance of anxiety provoking situations). Several parenting factors
likely play a role in the development of child anxiety, including parental beliefs, parenting
styles, and parenting behaviors.
While some aspects of the intergenerational transmission of anxiety may be due to
genetic factors, it is also likely that parental anxiety leads to certain environmental factors
that make children more vulnerable to anxiety. One potential mediator of parent and child
anxiety is parental beliefs. In a study of 103 youth with anxiety, researchers found that
parental beliefs about anxiety mediated the relationship between parent and child anxiety
(Francis & Chorpita, 2011). Parenting styles have also been examined. Craske (1999)
suggested that while parenting styles may activate trait anxiety, parenting behaviors may
lead to the development of an anxiety disorder.
Parental control, characterized by over-involvement in activities, routines, or
emotional experience, has also been examined as a factor in child anxiety. Parental control
may act by reducing a child’s sense of control of the environment, which can lead to anxiety
(Barlow, 2000; Becker, Ginsburg, Domingues, & Tein, 2010; Chorpita, Brown, & Barlow,
1998). In a meta-analysis of parenting and child anxiety, researchers found that child
anxiety was more strongly associated with parental control than with parental rejection;
parental autonomy granting and child anxiety had an average correlation of -0.42 (McLeod,
34
Wood, & Weisz, 2007). McLeod and colleagues (2007) found that parenting accounted for
about 4% of the variance in child anxiety, which suggests that while parenting and family
factors play a role in the development of anxiety, they likely interact with other factors,
such as the child’s age, biological vulnerability, and other life events (Creswell et al., 2011;
Murray et al., 2009).
Developmental psychopathology model of anxiety. The developmental
psychopathology model of anxiety posits the concept of multideterminism: there are a wide
range of causal influences for the development of anxiety that are complex, dynamic, and
interact with each other (Vasey & Dadds, 2000). Vasey and Dadds (2000) suggest that the
risk and protective factors for anxiety interact and influence each other in a transactional
manner. They also present the concepts of multifinality and equifinality. Multifinality
posits that any risk or protective factor can lead to multiple outcomes; for example
childhood maltreatment, punishment, parental psychopathology, low socioeconomic
status, and harsh parenting are non-specific risk factors for all mental health disorders
(Craske & Stein, 2016). Complimentary to this concept is that of equifinality, which states
that there are multiple pathways to the same outcome (Vasey & Dadds, 2000).
Vasey and Dadds (2000) propose an integrative model of developmental
psychopathology that suggests that cumulative risk for anxiety is created from a balance of
the transactional influences of risk and protective factors. They also suggest that there are
two pathways to anxiety: one in which there are clear precipitating events (e.g.,
conditioning or exposure to stressful events) and another in which symptoms of anxiety
35
gradually intensify over time (Vasey & Dadds, 2000). In addition to the risk and protective
factors that influence the development of anxiety, Vasey and Dadds (2000) also highlight
factors that contribute to the maintenance and intensification of anxiety. These factors
include: avoidance, incompetence across different skill domains (e.g. academic, emotion-
regulation, social), cognitive biases and distortions, punishment and failure, and responses
by others that influence avoidance (e.g., overprotection) (Vasey & Dadds, 2000). They
propose that temperament and developmental status can alter the degree to which these
factors influence anxiety (Vasey & Dadds, 2000). Additionally, Vasey and Dadds (2000)
suggest that “desistance” of anxiety can be promoted through opposite and complimentary
factors (e.g., exposure, cognitive restructuring).
Treatment of anxiety. Anxiety disorders in children are commonly treated through
therapy and medication. Cognitive behavioral therapy (CBT) is an effective treatment for
anxiety disorders in youth that generally includes psychoeducation, cognitive restructuring,
coping skills training, and graduated exposures (Compton et al., 2010). In a review of
treatments for youth with anxiety, well-established treatments with strong empirical
support included CBT with exposure, exposure-only, modeling, CBT with parents, and
CBT with medication (Higa-McMillan, Francis, Rith-Najarian, & Chorpita, 2016).
Common practice elements that are aspects of the most well-established treatments include:
exposure (87.9%), cognitive techniques (53.9%), relaxation (53.9%), psychoeducation
(42%), and modeling (33.9%) (Higa-McMillan et al., 2016). Therapy that included
36
exposure-based approaches had larger effect sizes, more durability, and more current
support in the literature (Higa-McMillan et al., 2016).
Selective serotonin-reuptake inhibitors (SSRIs) are the most common medications
prescribed to treat anxiety in youth; however, there is still limited research regarding the
safety and durability of these medications in children (Compton et al., 2010). Walkup and
colleagues (2008) compared treatment with CBT alone, sertraline alone, a combination of
sertraline and CBT, and placebo in a large multicenter randomized study of 488 children
and adolescents between the ages of 7 and 17. Researchers found that combination therapy
of sertraline and CBT led to the most improvement in anxiety symptoms, with 80.7% of
children on combination treatment being very much or much improved, compared to 59.7%
with CBT alone, 54.9% with sertraline alone, and 23.7% with placebo (Walkup et al.,
2008). These findings suggest that SSRIs and CBT are effective treatments, but a
combination of medication and therapy leads to the most improvement in anxiety
symptoms.
Quality of life in anxiety. Anxiety has significant effects on an individual’s quality
of life. Childhood anxiety not only predicts anxiety in adolescence and adulthood, but
anxiety can also be a predictor of other mental health problems in adulthood (Rapee,
Schniering, & Hudson, 2009). In a meta-analysis of 23 studies, researchers found that
individuals with anxiety had overall poorer quality of life than control subjects (Olatunji et
al., 2007). Additionally, individuals with anxiety are particularly affected across the mental
health and social functioning domains (Olatunji et al., 2007). In a study of 310 children
37
with a variety of psychopathology, researchers found that children with anxiety were most
affected in the emotional domain of quality of life (Bastiaansen, Koot, Ferdinand, &
Verhulst, 2004). Effective treatment of anxiety with medication is associated with
improvements in quality of life and greater anxiety symptom reduction is associated with
better improvement in quality of life (Hofmann, Wu, Boettcher, & Sturm, 2014). Treatment
with cognitive behavioral therapy is also associated with moderate improvements in quality
of life, particularly in the physical and psychological domains (Hofmann, Wu, & Boettcher,
2014).
Anxiety in Pediatric Epilepsy
The forgotten disorder. The prevalence of anxiety in individuals with epilepsy
appears to be elevated compared to rates of anxiety in the general population (Scott,
Sharpe, Hunt, & Gandy, 2017). This higher prevalence may be driven by both biological
and psychosocial factors. Many researchers have suggested that there is a bidirectional
relationship between anxiety and epilepsy, which can be driven by the biological correlates
of anxiety and epilepsy (Adelöw et al., 2012; Kanner, 2009). Additionally, there are
multiple psychosocial impacts of epilepsy that may lead to worry, including the impact of
epilepsy on independence, school functioning, and relationships (Scott et al., 2017).
Despite these biological, psychosocial, and environmental risk factors for anxiety in
individuals with epilepsy, anxiety is still considered the “forgotten” disorder and has been,
until more recently, widely ignored in the epilepsy research (Gandy et al., 2015).
Symptoms of anxiety may be particularly missed in pediatric patients with epilepsy
38
because children with anxiety may not be able to verbalize their feelings and may present
with disruptive or irritable behaviors (Ettinger et al., 1998). Scott and colleagues (2017)
emphasize the importance of more research to elucidate the medical and psychosocial risk
factors of anxiety in epilepsy in order to improve quality of life.
Prevalence of anxiety in epilepsy. Rates of anxiety in children and adolescents
with epilepsy range from 5% to 38.5% (Berg et al., 2011; Caplan et al., 2005; J. E. Jones
et al., 2007; Kwong et al., 2016; Reilly, Atkinson, Chin, et al., 2015; Russ et al., 2012;
Schraegle & Titus, 2017b, 2017a; Williams et al., 2003). Reasons for the discrepancies in
rates of anxiety may be related to methodological differences. In a study of 501 children
with epilepsy recruited from 16 pediatric neurologists in Connecticut, Berg et al. (2011)
found low rates of anxiety (5%); however, this study relied on parents to indicate whether
or not their children had a variety of different psychopathologies approximately 9 years
after epilepsy diagnosis. In contrast, through the use of a diagnostic interview, Jones and
colleagues (2007) found rates as high as 38.5% in a study that included 53 children with
recent onset idiopathic epilepsy recruited from two pediatric neurology clinics in
Wisconsin. In a recent meta-analysis studying prevalence of anxiety and depression in
adults with epilepsy, Scott and colleagues (2017) found that prevalence rates of anxiety
varied based on method of diagnosis. Prevalence of anxiety was 8.1% in studies that
utilized clinician judgement compared to a prevalence rate of 26.9% in studies that utilized
a structured clinical interview, suggesting that clinicians may underestimate the prevalence
of anxiety in individuals with epilepsy (Scott et al., 2017).
39
Anxiety is much more prevalent in children with epilepsy compared to heathy
children or children with other chronic health conditions (Russ et al., 2012). In a national
survey of over 90,000 children, 17% of children with epilepsy/seizure disorders were
reported by their parents to experience anxiety compared to just 3% of children without
epilepsy (Russ et al., 2012). Jones and colleagues (2007) compared 53 children with recent
onset idiopathic epilepsy and 50 healthy controls using a diagnostic interview (KSADS)
and found that 35.8% of children with epilepsy had anxiety compared to 22% of healthy
controls. Additionally, they found that 45% of children with epilepsy had an onset of a
psychiatric diagnosis before their first seizure and one third of these diagnoses were anxiety
(Jones et al., 2007). In a study of 101 adolescents with epilepsy in Jordan, the odds ratio
for anxiety was 3.66 when compared to healthy controls (Alwash et al., 2000). In a meta-
analysis of anxiety in children with chronic illness, researchers suggested that children with
epilepsy are one of the groups with the highest risk for anxiety symptoms and found the
effect size was significantly elevated (d=.34) (Pinquart & Shen, 2011). While anxiety is
prevalent in youth with anxiety, relatively few children receive adequate treatment. Caplan
and colleagues (2015) found that of children with affective or anxiety disorders and suicidal
ideation, only 33% were receiving mental health services.
Prevalence of specific anxiety diagnoses. In an MRI study of children with recent-
onset epilepsy, 12.5% had a diagnosis of specific phobia, 9.1% had a diagnosis of
separation anxiety, 6.8% had a diagnosis of social anxiety, and 5.7% had a diagnosis of
generalized anxiety (Jones et al., 2015). A recent meta-analysis of depression and anxiety
40
in adults with epilepsy found the pooled prevalence of generalized anxiety to be 10.2%,
social phobia was 5.3%, agoraphobia was 2.8%, panic disorder was 2.6%, and specific
phobia was 1.3% (Scott et al., 2017).
Risk and protective factors for anxiety in pediatric epilepsy. Pinquart and Shen
(2011) offer a variety of reasons for why children with a chronic illness may experience
anxiety, including: confrontation with dangerous stimuli (e.g., seizures), increased fear of
death, reduced control of the environment, uncertainty of illness and symptoms, risk of
peer rejection and associated social anxiety, parental over-protectiveness, and illness
symptoms that are similar to anxiety symptoms.
The etiology of anxiety in pediatric epilepsy is multifactorial, and likely involves
psychosocial, biological, and familial factors (Jones et al., 2015). Herman and colleagues
(1988) suggest a multietiological framework that integrates four hypotheses to understand
the greater prevalence of psychopathology in epilepsy. First, they suggest that there are
biological variables that are related to the cause, course, or outcome of the epilepsy that
also affect psychopathology (Hermann, Whitman, Hughes, Melyn, & Dell, 1988). Second,
Herman and colleagues (1988) suggest that psychosocial factors, such as stigma,
discrimination, and loss of social support, create stress that make individuals with epilepsy
more susceptible to psychopathology. Next, epilepsy medications may provide some risk
for psychopathology. Finally, demographic variables, such as age, education, sex, and race,
may be important factors to consider. This multietiological framework continues to be used
when considering the risk and protective factors for anxiety in epilepsy; however, the
41
framework has recently been expanded to include family factors, such as parenting, family
functioning, and parental psychopathology.
Biological correlates of anxiety in epilepsy. There are several aspects of brain
dysfunction in epilepsy that may contribute to higher symptoms of anxiety. Depending on
the location affected, seizures themselves may cause anxiety symptoms in individuals with
epilepsy. The limbic system, which includes the amygdala and the hippocampus, is a brain
region that is highly related to both anxiety and epilepsy. Common dysfunction in
neurotransmitter pathways may also contribute to the higher prevalence of anxiety in
individuals with epilepsy. Finally, there is emerging evidence that anxiety and epilepsy
have a bidirectional relationship.
Seizures. Seizures are defined by four distinct phases: pre-ictal, ictal, post-ictal, and
inter-ictal. Symptoms of anxiety can occur during any aspect of the seizure experience:
ictally, postictally, or interictally. The pre-ictal period is defined as the time immediately
prior to the seizure. The ictal period, or ictus, is the period of time when the seizure is
occurring. Anxiety can occur during the ictal period when a person experiences fear during
a seizure; this can be especially prevalent in individuals with temporal lobe epilepsy when
a seizure causes amygdala activation (Beyenburg, Mitchell, Schmidt, Elger, & Reuber,
2005). Seizures that propagate from other limbic structures, such as the orbitofrontal cortex
or the cingulate gyrus, also can lead to ictal fear (Biraben et al., 2001). The post-ictal period
is the time immediately after a seizure. Immediately after a seizure, individuals with
epilepsy might be confused or disoriented, which can lead to anxious symptoms
42
(Beyenburg et al., 2005). The inter-ictal period is the time between seizures. Individuals
with epilepsy might have symptoms of anxiety during the time between seizures for a
number of reasons, including: phobia of seizures, problems with adjustment, side effects
of medication, or surgical consequences (Beyenburg et al., 2005). Anxiety that occurs
immediately before, during, or after the seizure is generally transitory; anxiety that occurs
during the inter-ictal period will be the primary focus of this dissertation.
Prefrontal cortex. In an MRI study of 44 children with complex partial seizures,
researchers found significantly smaller inferior frontal white matter volumes in children
with a psychiatric diagnosis compared to those without (Daley et al., 2007). In a sample of
88 children with recent-onset epilepsy and 49 healthy controls, Jones and colleagues (2015)
found that children with epilepsy and anxiety had significantly thinner cortex in the right
frontal pole, right orbital frontal cortex, and left medial orbital frontal cortex. These studies
suggest that the prefrontal cortex may develop differently in children with both epilepsy
and anxiety.
Amygdala. The amygdala is at the forefront of research relating epilepsy and
psychopathology. Emotional symptoms, such as fear and palpitations, may emerge when
the amygdala is activated during a seizure (Yilmazer-Hanke, O’Loughlin, & McDermott,
2016). Researchers suggest that the amygdala may also be important to the inter-ictal
experience of anxiety in epilepsy, particularly in patients with temporal lobe epilepsy
(Yilmazer-Hanke et al., 2016). In an MRI study of 28 children with cryptogenic epilepsy
and complex partial seizures (CPS), researchers found no significant differences in
43
amygdala volumes between the epilepsy and control group, but found that children in the
CPS group with affective and anxiety disorders had greater asymmetry in the amygdala
and significantly larger left amygdala volume compared to children without
psychopathology (Daley et al., 2008). Jones and colleagues (2015) also found significantly
larger left amygdala volume in children with epilepsy and anxiety. In a study of 26 children
with absence epilepsy, Cohen (2009) found that amygdala volume was not related to an
affective or anxiety disorder diagnosis and suggested that this may be related to the shorter
duration of illness in children with epilepsy. Overall, there is some evidence that suggests
that children with epilepsy are at risk for or may have differences in amygdala volume.
Neurotransmitters. Serotonin and the 5HT receptors have been consistently
associated with symptoms of anxiety (Lesch et al., 1996; Martin et al., 2009; Vaswani et
al., 2003) and research has shown that there are abnormalities in these receptors in
individuals with temporal lobe epilepsy (Merlet et al., 2004; Savic et al., 2004; Toczek et
al., 2003). In a study using PET imaging, individuals with temporal lobe epilepsy had
reduced serotonin receptor binding in the area of seizure focus (Toczek et al., 2003). Other
researchers have shown that the regions affected by reduced receptor binding expand to
areas of the limbic system, including the hippocampus, amygdala, anterior cingulate,
insula, and raphe nuclei (Savic et al., 2004). Merlet et al. (2004) found that reduced receptor
binding was greater in the areas of seizure onset as well as in the areas where the seizure
propagated. Interestingly, some antiepileptic drugs, such as pregabalin, have been shown
44
to reduce symptoms of anxiety by the modulation of calcium ion channels and the
potentiation of GABAergic inhibition (Mula, Pini, & Cassano, 2007).
Bidirectional relationship. Many researchers have suggested that there is a complex
and bidirectional relationship between anxiety and epilepsy (Adelöw et al., 2012; Kanner,
2009). In a review of seizure incidence in psychopharmacological clinical trials,
researchers found high rates of seizures in the control condition, suggesting that seizure
risk may be related to psychopathology (Alper, Schwartz, Kolts, & Khan, 2007).
Additionally, in a review of hospitalization records, Adelöw and colleagues (2012) found
a 2.7 odds ratio for an unprovoked seizure in individuals discharged with a diagnosis of
anxiety. Jones and colleagues (2007) found that 45% of children with epilepsy had a
psychiatric diagnosis before their first seizure and suggested that antecedent
neurobiological factors may cause both anxiety and epilepsy. A bidirectional relationship
between epilepsy and anxiety is supported in research completed with rats with epilepsy
that exhibited anxious behaviors prior to the onset of seizures (N. C. Jones et al., 2008).
Cramer, Brandenburg, and Xu (2005) suggest that higher rates of anxiety and depression
in individuals with temporal-lobe epilepsy are due to common limbic pathways and
neurotransmitters. Research suggests that while a causal relationship may exist between
anxiety and seizures, there may also be a common underlying biological vulnerability for
anxiety and seizures in individuals with epilepsy.
Seizure variables. Seizure related variables, such as duration of epilepsy, number
of AEDs, seizure frequency, seizure control, seizure type, and age of seizure onset have
45
been consistently examined to determine their relationship to child psychopathology and
anxiety. Results from this research is inconclusive, with some studies indicating that
seizure and epilepsy related variables contribute to anxiety, while others find other
environmental factors to be more predictive of anxiety.
Epilepsy or seizure severity. Several researchers utilized an epilepsy severity
composite to approximate the impact of multiple seizure related variables. In a study of
501 children with epilepsy, researchers found that neurodevelopmental and psychiatric
disorders were more prevalent in individuals with complicated epilepsy (Berg et al., 2011).
However, in a study of 91 children with epilepsy Rodenburg et al. (2006) found that
epilepsy factors did not significantly predict internalizing problems. Jones and colleagues
(2015) echo these findings and determined that seizure severity did not differ significantly
in children with or without anxiety in youth with recent onset epilepsy. The variability in
the results regarding epilepsy severity are likely due to differences in how severity is
defined.
Duration of epilepsy and age of onset. Findings are also mixed when duration of
epilepsy is considered. In a comparison of 35 children with epilepsy and 35 healthy
controls, Oguz and colleagues (2002) found that epilepsy duration was related to higher
anxiety. Caplan et al. (2008) found that in 69 children with childhood absence epilepsy
(CAE), children had a 1.35 greater chance of having a psychiatric diagnosis for each year
of their CAE diagnosis. However, in several other studies, duration of epilepsy was not
related to anxiety or general mental health (Buelow et al., 2003; Caplan et al., 2004; J. E.
46
Jones et al., 2015; Rodenburg et al., 2006; Schraegle & Titus, 2017a). Age of onset
consistently did not predict anxiety symptoms or general mental health in children with
epilepsy (Buelow et al., 2003; Caplan et al., 2004; Jones et al., 2015; Oguz et al., 2002).
Discrepancies may exist in the findings due to inadequate sample sizes, differing methods
of assessment, and the epilepsy types included in analyses. Additionally, duration of
epilepsy may be confounded by other variables, such as the child’s chronological age and
age of onset (Austin & Caplan, 2007).
Seizure control. Research is inconclusive regarding the relationship between
seizure control and anxiety. Researchers in Jordan found that psychiatric symptoms were
higher in adolescents with medically uncontrolled epilepsy (Alwash et al., 2000). Berg and
colleagues (2011) determined that after adjusting for externalizing behaviors and age,
having a 5-year remission status was associated with 43% lower prevalence of internalizing
symptoms. Schraegle and Titus (2017a) found that rates of anxiety were significantly
higher in youth with intractable epilepsy. However, Caplan and colleagues (2004) found
that prolonged seizures were not related to anxiety and Ott and colleagues (2001) also
found that seizure control was not related to psychopathology. The differences in findings
in the literature are likely attributed to the variety of definitions applied to seizure control
and the lack of a standardized and consistent terminology for this construct.
Seizure frequency. Seizure frequency has been consistently related to symptoms of
anxiety in the literature. In a study of 201 adults with epilepsy, high seizure frequency was
a risk factor for anxiety (Kimiskidis et al., 2007). In a study of 35 children with epilepsy
47
compared to healthy controls, Oguz et al. (2002) also found that daily seizures were related
to increased ratings of anxiety. Caplan and colleagues (2007) echo these findings in that
youth with absence epilepsy with higher seizure frequency were significantly more likely
to have a psychiatric diagnosis. In a review of differential diagnoses of psychiatric
disorders in children with epilepsy, Dunn and Austin (2004) emphasized the importance of
seizure frequency. While most evidence suggests that seizure frequency is related to
psychopathology in youth with epilepsy, small sample sizes and relatively few studies
examining anxiety in youth make it difficult to fully understand the role of seizure
frequency in anxiety symptoms.
Medication. There are a variety of anti-epileptic medications that can be used to
treat epilepsy and most studies are not powered to review differences between medications.
Therefore, most research examining anxiety and AEDs has focused on a comparison of
monotherapy and polytherapy. Caplan and colleagues (2004) did not find a relationship
between AED type and anxiety. Additionally, Jones and colleagues (2015) determined that
the number of AEDs did not differ significantly in children with or without anxiety.
Alternatively, in a study of 101 children with epilepsy, researchers found that the number
of AEDs taken was a predictor of anxiety (Williams et al., 2003). Oguz (2002) also found
that polytherapy was related to higher symptoms of anxiety. Polytherapy was also a risk
factor for anxiety in adolescents and adults in Nigeria (Adewuya & Ola, 2005; Fatoye,
Mosaku, Komolafe, & Adewuya, 2006). Interestingly, Schraegle and Titus (2017a) found
that number of AEDs did not predict anxiety in youth who had parents with a positive
48
history of psychopathology, but polytherapy did significantly predict anxiety in youth with
parents who had no history of psychopathology. In a recent review, Reilly and colleagues
(2013) suggested that increased use of AEDs leads to an increased risk for anxiety in
children. However, in a recent meta-analysis of adults with epilepsy, Scott and colleagues
(2017) found that rates of anxiety were not higher in individuals with epilepsy who were
treated with polytherapy. It is unclear whether the effects of polytherapy would be similar
for youth and adults due to the confounds of age and length of AED treatment.
Additionally, it is difficult to distinguish whether higher rates of anxiety in individuals
taking polytherapy are due to side effects of multiple medications or because polytherapy
is an indication of more complex and difficult to control seizures, or a combination of these
factors (Austin & Caplan, 2007).
Seizure type and focus. Understanding differences in rates of anxiety based on
seizure type and focus would provide important information regarding the neurobiology of
anxiety; however, to date, the research is limited. In a study comparing children with
complex partial seizures and children with childhood absence epilepsy, Caplan and
colleague (2005) found that there was a higher rate of anxiety in children with absence
epilepsy. In a study of 48 children with complex partial seizures, 39 children with primary
generalized epilepsy with absence seizures, and 59 healthy controls, researchers found that
children with epilepsy had higher rates of psychopathology compared to healthy controls,
but rates of psychopathology did not differ between the two groups with epilepsy (Ott et
al., 2001). In a sample of 40 children with epilepsy who were examined prior to epilepsy
49
surgery, researchers found that there was no difference in rates of anxiety in children with
temporal lobe epilepsy compared to children with other epilepsy types (Salpekar et al.,
2013). Oguz et al., (2002) also did not find a relationship between epilepsy type and
anxiety. In a study of 501 children with epilepsy, researchers found that specific subtypes
of epilepsy were not related to specific psychiatric symptoms, which suggests that epilepsy
has a more broad and general impact on psychopathology (Berg et al., 2011). Overall, while
the number and quality of studies examining pediatric anxiety in epilepsy are limited,
tentative findings suggest that rates of anxiety do not differ based on seizure type nor focus
in children with epilepsy, but more research is needed.
Summary of seizure related variables. Austin and Caplan (2007) suggest that it is
difficult to understand the effects of seizure related variables due to the fact that they are
inter-related. Polytherapy, early age of onset, and poor seizure control are frequently inter-
related and can be confounding (e.g., an individual with poor seizure control may be placed
on multiple anti-epileptic medications and younger age of onset is associated with
uncontrollable seizures) (Austin & Caplan, 2007). Additionally, Austin and Caplan (2007)
note that a child’s chronological age might also be confounded by duration of illness and
age of onset (e.g., a younger child would have an early age of onset and likely shorter
duration).
In a recent review of anxiety in youth with epilepsy, Reilly, Kent, and Neville
(2013) concluded that some seizure variables, such as taking more than one AED, high
seizure frequency, and poor seizure control were consistently associated with higher scores
50
on measures of anxiety. Other seizure variables, such as seizure type, age of seizure onset,
and duration of epilepsy were not related to anxiety, but these findings were inconsistent
across studies (Reilly et al., 2013). In a review of psychiatric disorders in children and
adolescents with epilepsy, Dunn and Austin (2004) suggested that seizure syndrome,
seizure severity, seizure frequency, AEDs, and family variables such as family mastery and
control might be important variables to consider. They also indicated that seizure type was
inconsistently predictive of psychiatric disorders (Dunn & Austin, 2004). It is clear that
some seizure related variables may affect psychopathology and anxiety in children with
epilepsy. However, sample sizes have been small and there are relatively few studies that
examine anxiety in youth with epilepsy. More research is needed to determine whether
seizure related variables have a direct effect on psychopathology or if they moderate or
mediate other psychosocial variables.
Demographic variables. Age, gender, and ethnicity are consistently examined to
determine whether there are differences in levels of anxiety based on these demographic
variables. Oguz and colleagues (2002) found that younger children (ages 9-11) had higher
ratings of trait anxiety while adolescents (ages 12-18) had higher levels of both state and
trait anxiety. In a population-based study of 69 children with active epilepsy, researchers
found that anxiety symptoms were higher for older children (Reilly, Atkinson, Chin, et al.,
2015). In a study of 180 youth with epilepsy, older age and female gender both significantly
predicted anxiety (Schraegle & Titus, 2017a). Schraegle and Titus (2017b) found that
several demographic variables were related to higher anxiety symptoms, including age
51
(older), sex (females), and race/ethnicity (minorities). Williams et al. (2003) also found
that ethnicity was a predictor of anxiety in children with epilepsy. In a study of 69 children
with absence epilepsy and 103 controls, Caplan and colleagues (2008) found that girls were
5.8 times more likely to have anxiety than boys. Age and gender appear to be important
demographic variables to consider when examining anxiety in youth with epilepsy.
Cognitive ability. Cognitive ability is also an important variable to consider when
examining anxiety in youth with epilepsy. In a study comparing 171 kids with epilepsy,
Caplan et al. (2015) found that children with epilepsy who had co-occurring affective and
anxiety disorders had significantly lower IQs compared to children with epilepsy and no
disorder. In a study of 164 youth with epilepsy, researchers found that there were more
mental health problems in the group of children with low IQ (Buelow et al., 2003).
Researchers have also found that comorbid learning problems are related to anxiety in
youth with epilepsy (Williams et al., 2003). Cognitive factors are likely confounded by
seizure related variables; for example, youth with epilepsy and a high IQ are more likely
to have a shorter duration of illness and less severe seizures (Buelow et al., 2003).
Stigma. Individuals with epilepsy experience high levels of stigma, however,
research examining the relationship between stigma and anxiety in youth with epilepsy is
severely limited. Davies and colleagues (2003) suggest that there are higher rates of
psychiatric diagnoses in children with epilepsy compared to other chronic illnesses because
of the social stigma of epilepsy. Youth with epilepsy are also at risk for peer rejection,
which can lead to experiences of social anxiety (Pinquart & Shen, 2011). Child perceptions
52
of stigma are related to greater child fear and worry about seizures (Austin et al., 2014).
Additionally, parent and adolescent perceptions of stigma were both significant predictors
of anxiety symptoms in a sample of 102 adolescents in Nigeria (Adewuya & Ola, 2005).
Evidence of the role of stigma in anxiety is sparse, but preliminary evidence suggests a
relationship between anxiety and perceptions of stigma.
Family variables. Family factors, such as parent-child relationships, family
adaptation, parental psychopathology, and family stressors, play an important role in the
development of anxiety in children with epilepsy. Only one study to date has examined the
association between parent-child relationships and psychopathology in youth with
epilepsy. Positive parent-child relationships were related to lower parent reported
symptoms of internalizing and externalizing problems in children with epilepsy, while
parental rejection led to increased ratings of internalizing and externalizing problems
(Rodenburg et al., 2006). Rodenburg and colleagues (2006) also found that parental
rejection mediated the relationship between problems with family adaptation and
symptoms of anxiety and depression, meaning that poorer family adaptation leads to parent
rejection which ultimately leads to more symptoms of anxiety/depression (Rodenburg et
al., 2006). In general, family stressors are associated with higher rates of anxiety in youth
with epilepsy (Adewuya & Ola, 2005; Schraegle & Titus, 2017a).
Parent history of psychopathology is another important predictor of child anxiety
due to its genetic and environmental influences. In a recent review, Jones and Reilly (2016)
found that parents of children with epilepsy and anxiety commonly have symptoms of
53
anxiety. In a study of 88 children with recent-onset of epilepsy and 49 health controls,
71% of children with epilepsy who were diagnosed with anxiety had a family member with
a history of anxiety or depression, which was significantly different when compared to
children with epilepsy without anxiety (37%) and control subjects (25%) (Jones et al.,
2015). Adewuya and Ola (2005) also found that youth anxiety was related to parental
psychopathology. In a recent analysis of 180 children with epilepsy, Schraegle and Titus
(2017a) found that parental psychiatric history was related to a 3-fold risk for anxiety; this
increased to a 4-fold risk for anxiety in the context of intractable epilepsy. Schraegle and
Titus (2017a) also found that the factors that contribute to anxiety differ in the context of
parental anxiety (e.g., AEDs were related to anxiety in those children with a parent with no
psychiatric history, but AEDs were unrelated to anxiety in children with a parent with
psychiatric history). Parent anxiety is common in children with epilepsy and it is associated
in lower quality of life (C. Jones & Reilly, 2016; Schraegle & Titus, 2017b). Despite the
importance of family factors on child anxiety in the literature, research in youth with
epilepsy is limited.
Anxiety and health related quality of life in epilepsy. Health related quality of
life (HRQoL) is an individual’s perceptions of quality of life relative to their health or
disease status (Bakas et al., 2012). In a prospective, community-based study, psychiatric
comorbidity in child-onset epilepsy was more highly correlated with HRQoL than
remission status (Baca, Vickrey, Caplan, Vassar, & Berg, 2011). Additionally, Baca and
colleagues (2011) found that internalizing psychiatric comorbidity was associated with
54
worse HRQoL, while externalizing symptoms had no relationship to HRQoL. In a study of
60 children with epilepsy in Serbia, researchers found that depression, generalized anxiety
symptoms, and separation anxiety symptoms had the most significant impact on quality of
life compared to other demographic and epilepsy variables (Stevanovic et al., 2011). When
examining domains of quality of life, lower internalizing symptoms were related to better
physical and emotional quality of life (Loiselle et al., 2016). In a study of HRQoL in 109
children with pediatric epilepsy after surgery, researchers found that improved seizure
freedom in the last twelve months was associated with better HRQoL and that symptoms
of anxiety and depression mediated this relationship; in other words, seizure freedom led
to better parent ratings of anxiety and depression which led to better HRQoL (Puka &
Smith, 2015). Symptoms of anxiety in youth with epilepsy have significant effects on
quality of life.
Statement of the Problem and Purpose
There are a multitude of factors that put youth with epilepsy at an increased risk of
anxiety, including biological, psychosocial, demographic, and family factors; these factors
likely interact and influence each other. Despite the clear relationship between anxiety and
epilepsy, anxiety has been considered the “forgotten” disorder in epilepsy research and has
been overshadowed by research in depression (Clary, 2014). In the research that has been
conducted about anxiety in youth with epilepsy, there has been no underlying theoretical
background for the selection of variables and researchers have used inappropriate measures
(Gandy, Sharpe, & Perry, 2012). Additionally, in clinical care anxiety is severely
55
underdiagnosed and only a third of diagnosed children actually receive mental health
services (Caplan et al., 2005). Furthermore, a recent ILAE Task Force Report suggested
that it is important to assess for reversible causes of anxiety (Dunn et al., 2016). Examining
family factors and psychosocial difficulties associated with anxiety in youth with epilepsy
is especially important because it may help to identify accessible and modifiable targets
for intervention. There is a clear need for more research investigating the risk and
protective factors for anxiety in youth with epilepsy. This proposed research study will
examine how seizure severity and parent factors (i.e., history of psychopathology, illness
cognitions, and perceptions of stigma) interact to influence anxiety in youth with epilepsy.
Research Questions and Hypotheses
Research question 1. To what extent do parent factors influence anxiety in youth
with epilepsy?
Hypothesis 1a. Youth with epilepsy who have a parent with a history of
psychopathology will have more parent reported anxiety features.
Rationale 1a. Parent psychopathology is an important predictor of child anxiety
due genetic and environmental factors. Heritability estimates are in the range of 30-40%
for anxiety (Hettema et al., 2001; Micco et al., 2009). Parent history of psychopathology
may also lead to environmental factors (e.g., socialization, modeling, and accommodation)
that make children more vulnerable to anxiety (Murray et al., 2009). In the general
population, children of parents with anxiety are four times more likely to have anxiety than
children without a parent with anxiety (Micco et al., 2009) and youth with epilepsy who
56
have parents with a history of psychopathology are also at increased risk for anxiety
(Adewuya & Ola, 2005; Jones et al., 2015; Schraegle & Titus, 2017a).
Hypothesis 1b. Elevated parent perceptions of stigma will be related to increased
parent reported anxiety features in youth with epilepsy.
Rationale 1b. Many researchers have hypothesized that higher rates of anxiety in
youth with epilepsy are related to the social stigma of epilepsy (Davies et al., 2003;
Hermann et al., 1988). However, relatively few studies have systematically examined this
issue. Some researchers have found that higher perceptions of stigma are related to more
worry (Austin, MacLeod, Dunn, Shen, & Perkins, 2004; Austin et al., 2014) and one
research group found that anxiety was predicted by both parent and adolescent perceptions
of stigma (Adewuya & Ola, 2005). Parents with higher perceived stigma may also engage
in more overprotective parenting behaviors that increase the risk for anxiety in children
(Anthony, Gil, & Schanberg, 2003).
Hypothesis 1c: Negative parent illness cognitions will be related to increased parent
reported anxiety features in youth with epilepsy.
Rationale 1c. Parent illness cognitions, particularly cognitions of helplessness, may
lead to higher rates of anxiety in children through several pathways, including increased
parent distress, modeling of anxious cognitions and behaviors, and parenting behaviors.
Negative parent illness cognitions and difficulty coping with a child’s illness are related to
parent distress, which is associated with emotional distress in the child (Colletti et al., 2008;
Nicolaas et al., 2016; Robinson, Gerhardt, Vannatta, & Noll, 2007; Steele, Dreyer, &
57
Phipps, 2004). Parents with cognitions of helplessness may model anxious behavior and
influence illness cognitions in their child (Burstein & Ginsburg, 2010) and individuals with
poor illness cognitions have poorer emotional health (Hudson, Bundy, Coventry, &
Dickens, 2014). A parent’s feelings of helplessness might also influence the child’s
perceptions of control over their environment (Chorpita & Barlow, 1998). Parents may also
engage in parenting behaviors, such as overprotection, which can make a child more
vulnerable to anxiety by limiting the child’s engagement in the environment (Anthony et
al., 2003).
In contrast to parent cognitions of helplessness, parent cognitions of acceptance
may be related to less distress, positive modeling, and parenting behaviors that are
protective factors for child anxiety. Parents who engage in acceptance cognitions may be
less distressed, which is associated with better emotional adjustment in children (Nicolaas
et al., 2016). Additionally, parents with cognitions of acceptance may model more adaptive
coping behavior and cognitions and engage in parenting behavior that allows the child to
engage in behaviors that increase their perceptions of control over their environment
(Burstein & Ginsburg, 2010; Chorpita & Barlow, 1998).
Research question 2. To what extent do parent factors mediate the effect of parent
history of psychopathology on anxiety in youth with epilepsy?
Hypothesis 2a: Parent perceptions of stigma will partially mediate the effect of
parent history of psychopathology on parent reported anxiety features in youth with
epilepsy.
58
Rationale 2a. Parents with a history of psychopathology will have more perceptions
of stigma, which will impact their ratings of child anxiety. Parents with more negative
mood are more likely to report greater perceptions of stigma (Austin et al., 2004). Parent
history of psychopathology will lead to negative perceptions of stigma, which will
ultimately lead to higher ratings of anxiety in youth with epilepsy.
Hypothesis 2b: Negative parent illness cognitions will partially mediate the effect
of parent history of psychopathology on parent reported anxiety features in youth with
epilepsy.
Rationale 2b. Parents with a history of psychopathology will have more negative
illness cognitions, which will impact their ratings of child anxiety. Parents who are
clinically distressed have more cognitions of helplessness and fewer cognitions of
acceptance (Nicolaas et al., 2016). Additionally, parent cognitions of helplessness are
correlated with worse psychological well-being, while parent cognitions of acceptance are
associated with better psychological well-being (Nicolaas et al., 2016). Parent history of
psychopathology will lead to negative illness cognitions, which will ultimately lead to
higher ratings of anxiety features in youth with epilepsy.
Research question 3. To what extent does seizure severity influence the impact of
parent factors on anxiety in youth with epilepsy?
Hypothesis 3a. Seizure severity will moderate the effect of parent history of
psychopathology on parent perceived stigma.
59
Rationale 3a. This hypothesis is supported by Austin et al. (2004), who found that
greater parent perceptions of stigma are associated with greater seizure severity.
Additionally, Schraegle and Titus (2017a) found differential effects of AEDs for parents
with and without a history of psychopathology. AEDs were related to anxiety in youth
without a parent with a history of psychopathology, but AEDS were not related to anxiety
in youth with a parent with a history of psychopathology (Schraegle & Titus, 2017a). There
may be a similar interaction between parent history of psychopathology and seizure
severity on parent perceptions of stigma. Parents with a history of psychopathology might
have higher perceptions of stigma regardless of their child’s seizure severity, while parents
with no history of psychopathology may only be at risk of higher perceptions of stigma in
the context of greater seizure severity. See Figure 3.
60
Figure 3: Hypothesized moderation on parent perceptions of stigma. This figure illustrates the hypothesized interaction between parent history of psychopathology and seizure severity on parent perceptions of stigma. The red line represents the hypothetical regression of seizure severity on parent perceptions of stigma in parents with a history of psychopathology, while the blue line represents the hypothetical regression of seizure severity on parent perceptions of stigma in parents without a history of psychopathology. A higher score indicates more negative perceptions of stigma.
Hypothesis 3b. Seizure severity will moderate the effect of parent history of
psychopathology on parent illness cognitions.
Rationale 3b. AEDs are a predictor of anxiety in youth with a parent with no history
of psychopathology, while AEDs are not a predictor of anxiety in youth with a parent with
a history of psychopathology (Schraegle & Titus, 2017a). Seizure severity may have a
similar interaction with parent history of psychopathology on parent illness cognitions.
Parents without a history of psychopathology may be more vulnerable to negative illness
cognitions in the context of greater seizure severity, while parents with a history of
psychopathology may be more susceptible to negative coping cognitions regardless of the
context. See Figure 4.
012345
Low Severity High Severity
No Parent History Psych. Yes Parent History Psych.
Pare
nt P
erce
ptio
ns o
f Stig
ma
61
Figure 4: Hypothesized moderation on parent illness cognitions. This figure illustrates the hypothesized interaction between parent history of psychopathology and seizure severity on parent illness cognitions. The red line represents the hypothetical regression of seizure severity on parent illness cognitions in parents with a history of psychopathology, while the blue line represents the hypothetical regression of seizure severity on parent illness cognitions in parents with a history of psychopathology. A lower score indicates more negative illness cognitions.
Research question 4. To what extent do family factors, anxiety, and seizure
severity influence quality of life in youth with epilepsy?
Hypothesis 4. Increased seizure severity, features of anxiety, parent perceptions of
stigma, and negative parent illness cognitions will be related to decreased health related
quality of life in youth with epilepsy.
Rationale 4. Many seizure variables, including polytherapy and increased seizure
frequency, have been associated with decreased quality of life in youth with epilepsy (Baca
et al., 2011; Conway et al., 2016; Puka & Smith, 2015). Internalizing symptoms, such as
anxiety and depression, have frequently been associated with decreased quality of life in
010203040506070
Low Severity High Severity
No Parent History Psych. Yes Parent History Psych.Pare
nt Il
lnes
s Cog
nitio
ns
62
individuals with epilepsy (Baca et al., 2011; Conway et al., 2016; Loiselle et al., 2016;
Puka & Smith, 2015; Reilly, Atkinson, Das, et al., 2015b; Stevanovic et al., 2011).
Moreover, some researchers suggest that internalizing symptoms have the most significant
effect on quality of life (Stevanovic et al., 2011) and that anxiety and depression mediate
the relationship between seizure control and quality of life (Puka & Smith, 2015). Research
into the effect of family factors is more limited, but some research suggests that parent
anxiety is associated with decreased quality of life (Jones & Reilly, 2016; Schraegle &
Titus, 2017a).
Hypothesized model. Taken together, these hypotheses suggest that anxiety may
influenced by parent factors in several ways. First, parent history of psychopathology is
hypothesized to have a direct influence on anxiety through genetic and environmental
factors. Parent illness cognitions and parent perceptions of stigma are also hypothesized to
influence anxiety, and these parent factors are hypothesized to partially mediate the relation
between parent history of psychopathology and anxiety. Finally, seizure severity is
hypothesized to moderate the impact of parent history of psychopathology on parent
perceived stigma and parent illness cognitions. See Figures 5 and 6.
63
Figure 5: Hypothesized model including parent perceptions of stigma. This figure illustrates the hypothesized relations between parent history of psychopathology, parent perceptions of stigma, seizure severity, and anxiety in pediatric epilepsy.
Figure 6: Hypothesized model including parent illness cognitions. This figure illustrates the hypothesized relations between parent history of psychopathology, parent perceptions illness cognitions, seizure severity, and anxiety in pediatric epilepsy.
It is important to note that this is a cross-sectional study and the data used in this
research are nonexperimental in nature; there was no experimental manipulation of seizure
severity, parent perceptions of stigma, parent illness cognitions, or parent history of
64
psychopathology to determine their subsequent effect on parent reported anxiety.
Therefore, all statements that discuss the “effect” or “influence” of one variable on another
are dependent on the validity of this model. “If the model is a reasonable representation of
reality, the estimates resulting from the model indeed show the extent of the influence of
one variable on another. If the model is not a reasonable representation of reality, the
estimates are not accurate estimates of those effects.” (Disclaimer adapted from Keith
[2014]).
65
Chapter 3: Methods
Participants
Participants in this study included 121 children and adolescents with epilepsy who
were referred to a tertiary outpatient clinic in Central Texas by their neurologists for a
neuropsychological evaluation to assist with treatment planning. Youth were considered
for inclusion in the study if they were between the ages of 6-18 and were diagnosed with
epilepsy by a neurologist. Youth were excluded from the study if the caregiver or child did
not speak English or if the parent or caregiver did not consent for their child’s information
to be used for research purposes.
Procedures
Parents of youth with epilepsy who were referred for neuropsychological
evaluation were consented during the assessment intake. The primary caregiver was asked
to complete an intake questionnaire and measures related to their child’s health and
epilepsy. All parents also completed a clinical intake interview regarding their child’s
medical, psychosocial, and family history with a licensed psychologist. Medical records
were reviewed for all patients whose parents provided written and oral consent for their
results to be used for research purposes. Institutional review board approval was obtained
for all data collection procedures.
66
Measures
Demographic information. Demographic information was obtained via review of
medical records, intake questionnaires, and parent interviews. Variables included: gender,
race/ethnicity, child’s age, and maternal education (coded as 1= less than high school,
2=high school degree, 3= some college, 4=college degree, 5=graduate degree).
Seizure information. Seizure-related variables were extracted from medical
records, intake questionnaires, and parent interviews. Variables included: age at seizure
onset, duration of epilepsy, number of AEDs (coded as 0=no AED treatment,
1=monotherapy, 2=polytherapy), seizure frequency (coded as 0=none in past year,
1=yearly, 2=quarterly or monthly, 3=weekly or daily), epilepsy type (coded as 0=no
seizures in the past year, 1=absence seizures, 2=focal seizures, 3=generalized tonic-clonic,
4=multiple seizure types), and intractability status (coded as 0=not intractable and
1=intractable, using the ILAE task force definition of drug-resistant epilepsy) (Kwan et al.,
2010). Seizure severity was a composite variable, similar to the approach of Rodenberg et
al. (2006) and Austin et al. (1996), calculated as a sum of the values for epilepsy type,
number of AEDs, and seizure frequency.
Parent history of psychopathology. Information regarding parent history of
psychopathology was obtained from family history reported by parents on the intake
questionnaires and parent interviews. Parent psychiatric history was reviewed for presence
of anxiety, depression, and/or bipolar disorder and was coded as 1 (present) or 0 (absent).
67
Anxiety. Anxiety was measured using Parent Rating Scales (PRS) from the
Behavior Assessment System for Children (BASC) second and third editions (Kamphaus
& Reynolds, 2015; Reynolds & Kamphaus, 2004). A majority of parents completed the
BASC-3 (n=76; 62.8%). The BASC-3 contains all of the same items found on the BASC-
2 and includes some additional items. The BASC-2 and BASC-3 anxiety scales are very
highly correlated (r=0.97-0.98) (Kamphaus & Reynolds, 2015). The BASC PRS Child
Form (ages 6:0-11:11) and the PRS Adolescent Form (ages 12:0-21:11) were used
depending on the age of the child during the assessment. The BASC PRS anxiety scale has
11 to 14 items that the parent rated according to the frequency of their child’s behavior
(never, sometimes, often, or almost always). Raw scores were converted to T-scores, with
T-scores of 60-69 considered in the “at risk” range and T-scores ≥70 considered in the
“clinically significant” range.
The BASC-2 was normed using 1,800 parents for each form version and the sample
was designed to represent the US population (from the 2001 Current Population Survey)
with respect to gender, race/ethnicity, socioeconomic status, geographic region, and special
education classification. The anxiety scale has good internal-consistency reliability
(coefficient alpha ranging from 0.81-0.85) and test-retest reliability (corrected r=0.73-
0.86). Inter-rater reliability is moderate (corrected r=0.66-0.80) (Reynolds & Kamphaus,
2004). The standard error of measurement ranges from 3.9 to 4.44 (Reynolds & Kamphaus,
2004).
68
The BASC-3 was normed using 600 parents for each form version and the sample
was designed to represent the US population with respect to gender, race/ethnicity,
socioeconomic status, geographic region, and special education classification. The anxiety
scale has good internal-consistency reliability (coefficient alpha ranging from 0.83-0.89)
and test-retest reliability (corrected r=0.85-0.90). Inter-rater reliability is moderate
(corrected r=0.54-0.65) (Kamphaus & Reynolds, 2015). The standard error of
measurement ranges from 3.32 to 4.12 (Kamphaus & Reynolds, 2015).
In terms of validity, the BASC has good internal structure. There are low to
moderate correlations between the BASC-3 anxiety scale and the AESEBA
Anxiety/Depression scale (r= 0.46-0.63) and between the BASC-2 anxiety scale and the
AESEBA Anxiety/Depression scale (r= 0.48-0.71). The BASC PRS has been widely used
in research with pediatric epilepsy populations (Bender et al., 2008; Titus, Kanive, Sanders,
& Blackburn, 2008; Vega et al., 2011).
Stigma. Parent perceptions of stigma were assessed using the Epilepsy Stigma
Scale (Austin et al., 2004). Stigma was defined by the authors of the measure as “referring
to an attribute (i.e., seizure condition) held by a person that leads to his or her being
discredited or devalued by others” (Austin et al., 2004). The parent version of the form
measures parent perceptions of how epilepsy affects others’ perceptions of their child
(Austin et al., 2004). The parent version of the Epilepsy Stigma Scale consists of five items
rated on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree),
with questions like “people who know my child has a seizure condition treat him/her
69
differently.” The items were summed and divided by the number of items to provide a
stigma score; a higher score reflected greater perceptions of stigma related to epilepsy
(Austin et al., 2004).
The psychometric properties of the scale were assessed with 171 parents of children
(ages 9-14) with chronic epilepsy and 224 parents of children (ages 4-14) with new-onset
epilepsy. Factor analysis of the stigma scale revealed that one factor accounted for 100%
of the variance, factor loadings for each question ranged from 0.63 to 0.84, and found flat
scree plots after the first factor; this suggests that the scale measures one unitary construct
(Austin et al., 2004). The Epilepsy Stigma Scale also demonstrates good internal
consistency (coefficient alpha ranging from 0.77-0.79) (Austin et al., 2004). In this sample,
the Epilepsy Stigma Scale demonstrated good internal consistency (Chronbach’s alpha
0.79). Overall, the Epilepsy Stigma Scale has good psychometric properties and appears to
measure one construct.
Illness cognitions. Parent illness cognitions were measured using the Illness
Cognition Questionnaire-Parent Version (ICQ-P) (Nicolaas et al., 2016). The ICQ-P was
adapted from the Illness Cognition Questionnaire (ICQ), which was originally developed
for adults with chronic health conditions (Evers et al., 2001). The ICQ-P measures a
parent’s cognitions about how they evaluate their child’s illness. The ICQ-P consists of
three subscales: helplessness (e.g., my child’s illness prevents me from doing what I would
really like to do), acceptance (e.g., I can cope effectively with my child’s illness), and
disease benefits (e.g., my child’s illness has helped me realize what is important in life)
70
(Nicolaas et al., 2016). The ICQ-P consists of 18 items rated on a 4-point Likert scale (1=
not at all, 2=somewhat, 3=to a large extent, 4=completely). The scores are calculated by
summing the items scores; subscale scores range from 6 to 24 and the total score ranges
from 18 to 72.
The psychometric properties of the scale were originally assessed with 242 parents
of children aged 0 to 17 with cancer (Nicolaas et al., 2016). Factor analysis revealed that
three factors accounted for 59.1% of the variance. Each subscale has adequate internal
consistency (Chronbach’s alpha 0.80-0.88) (Nicolaas et al., 2016). In this sample, it also
demonstrated adequate internal consistency for the total score (Chronbach’s alpha 0.71)
and for each subscale (Chronbach’s alpha 0.71-0.86). Parent cognitions of helplessness
were moderately correlated with worse psychological well-being and parents who were
clinically distressed had more cognitions of helplessness (Nicolaas et al., 2016). Parent
cognitions of acceptance were moderately to highly associated with better psychological
well-being and parents who were clinically distressed had fewer cognitions of acceptance
(Nicolaas et al., 2016). The ICQ-P has been used within the epilepsy population
(McLaughlin, Schraegle, Nussbaum, & Titus, 2016; McLaughlin, Schraegle, & Titus,
2017).
Quality of life. Health related quality of life (HRQOL) was measured using the
Quality of Life in Childhood Epilepsy (QOLCE) and the Quality of Life in Childhood
Epilepsy-55 (QOLCE-55), which are both parent reported measures of quality of life
designed specifically for children and adolescents with epilepsy ages 4-18.
71
The QOLCE consists of 91 items rated on a five-point Likert scale ranging from
“very often” or “all of the time” to “never” or “none of the time;” other questions range
from “yes, limited a lot” to “no, not limited” and “excellent” to “poor,” depending on item
content. The QOLCE measures HRQOL across a variety of functional life domains,
including: physical functioning, emotional well-being, cognitive functioning, social
functioning, and behavior (Sabaz et al., 2000). The QOLCE-55 was developed using a
principal component analysis of the QOLCE to reduce the number of items (Goodwin,
Lambrinos, Ferro, Sabaz, & Speechley, 2015). The QOLCE-55 consists of 55 items rated
on a five-point Likert scale ranging from “very often” or “all of the time” to “never” or
“none of the time;” other questions range from “yes, limited a lot” to “no, not limited,”
depending on item content. Factor analysis of the QOLCE-55 indicated a four-factor model
of HRQOL, including cognitive, emotional, social, and physical domains. The overall
QOLCE-55 score demonstrates high internal consistency (Cronbach's alpha =0.96), and
the individual subscales have similarly robust internal consistency (Cronbach's alpha =
0.82-0.97) (Goodwin et al., 2015). Convergent validity with theoretically similar constructs
is adequate (ρ = 0.38) (Goodwin et al., 2015).
Most parents completed the QOLCE-55 (n=82; 67.8%); however, for those that
completed the QOLCE, items were extracted and re-scored according to the QOLCE-55
due to its stronger psychometric properties (Goodwin et al., 2015). The QOLCE-55 was
scored using a linear transformation of raw scores to a 0–100-point scale, where higher
72
scores indicate a higher level of HRQOL. An overall quality of life score was calculated as
the sum of scores from all domains.
Cognitive functioning. Intelligence was assessed using the Wechsler Adult
Intelligence Scale-IV (WAIS-IV), the Wechsler Intelligence Scale for Children-IV (WISC-
IV), the Wechsler Intelligence Scale for Children-V (WISC-V), or the Kaufman
Assessment Battery for Children, Second Edition (KABC-II) based on the age of the child
at the time of testing and clinical judgment. The Wechsler intelligence scales and the
Kaufman Assessment Battery for Children are widely used measures of cognitive
functioning. The KABC-II is designed for use with children between the ages of 3:0 and
18:11. WISC-IV and WISC-V are designed for use with children between the ages of 6:0
and 16:11 and the WAIS-IV is designed for use in individuals between the ages of 16:00
and 90:11.
The WISC-IV and WISC-V were both normed on samples of 2,200 children
stratified on U.S. Census data (March 2000 for WISC-IV and October 2012 for WISC-V)
to match population characteristics related to age, sex, race/ethnicity, geographic region,
and self or parent education level. The WAIS-IV was normed on a sample of 2,200 adults
stratified by U.S. Census data (October 2005) to match population characteristics related
to age, sex, race/ethnicity, geographic region, and parent education level. The Full Scale
IQ (FSIQ) is a measure of global cognitive ability that is derived from seven subtests from
the WISC-V and WISC-IV. The FSIQ on the WAIS-IV is derived from ten subtests. The
reported internal reliability coefficient for the FSIQ is 0.96, 0.96, and 0.98 for the WISC-
73
IV, the WISC-V, and the WAIS-IV, respectively. The corrected r for test-retest reliability
for the FSIQ is 0.91, 0.92, and 0.96 for the WISC-IV, the WISC-V, and the WAIS-IV,
respectively (Wechsler, 2003, 2008, 2014). The KABC-II was normed on a sample of
3,025 children stratified on U.S. Census data (2001) to match population characteristics
related to gender, ethnicity, parent education, geographic region, and educational and
psychological classification (Kaufman & Kaufman, 2004). The Fluid-Crystalized Index
(FCI) is a composite measure of cognitive ability that is derived from ten subtests on the
KABC-II. The reported split-half reliability coefficient for the FCI on the KABC-II ranges
from .94 to .97. The adjusted r for test-retest reliability of the FCI on the KABC-II ranges
from .90 to .94 (Kaufman & Kaufman, 2004).
Most youth were assessed using the WISC-V (n=73; 60.4%). However, due to the
necessity to assess patients with epilepsy with the same instrument before and after
epilepsy surgery, some patients were administered the WISC-IV (n=8; 6.4%). There are
many similarities between the two versions of the WISC, but some of the subtests are not
identical and they were normed on different populations. The developers report strong
correlations between the FSIQ index on the WISC-IV and the WISC V (corrected r of 0.86)
(Wechsler, 2003, 2014). Some younger children were administered the KABC-2 (n=15;
12.4%), and there are moderate correlations between the FCI index on the KABC-II and
the FSIQ on the WISC-IV and the WISC V, (adjusted r=0.89 and r=0.81, respectively)
(Kaufman & Kaufman, 2004; Wechsler, 2014). Older adolescents were administered the
WAIS-IV (n=25; 20.7%), and there are also strong correlations on the FSIQ index between
74
the WAIS-IV and the WISC-IV (corrected r of 0.91) and between the WAIS-IV and the
WISC-V (corrected r of 0.89) (Wechsler, 2003, 2008, 2014).
Analyses
Preliminary analyses. Preparation of the data and preliminary analyses were
conducted using SPSS 22.0. Results of a power analysis indicated that to detect a small to
medium effect size of f2 = 0.1 with power of 0.80 at an alpha level of 0.01 a total of 121
participants were necessary (Faul, Erdfelder, Lang, & Buchner, 2007). Estimates for a
sample size needed for a bias-corrected bootstrap with a medium effect size for the a path
and a small to medium effect size for the b path was approximately 116 (Fritz &
MacKinnon, 2007). Descriptive statistics (means, ranges, standard deviations, minimum
and maximum values) were calculated for each of the criterion variables. Correlations
between all variables were also assessed.
Analysis of the research questions. Analyses consisted of a series of multiple
regressions and tests of mediation and moderation using the Hayes (2013) PROCESS
Macro in SPSS version 22.0. To ensure that no assumptions were violated, the data were
assessed for linearity, independence of errors, homoscedasticity (variance of errors),
normality of residuals, approximate normality of distribution, and outliers (Keith, 2014).
Statistical assumptions were examined, and no violations were detected. The data were also
assessed for multicollinearity by assessing tolerance (independence of independent
variables) and the variance inflation factor (Keith, 2014).
75
PROCESS is a free statistical tool for use on SPSS that completes mediation and
moderation analyses using path-analysis. The PROCESS mediation model uses
bootstrapping, which is a resampling method, to determine indirect effects. Bootstrapping
generates an “empirically derived representation of the sampling distribution of the indirect
effect,” which is then used to generate a confidence interval for the indirect effect (Hayes,
2013). PROCESS uses a bias-corrected bootstrap confidence interval (using 10,000
bootstrap samples), which is a recommended approach for inferring indirect effects in
mediation analyses (Hayes, 2013). Bootstrapping is the generally preferred method
compared to Sobel tests (or the normal theory approach) in mediation analyses because it
has higher power (less conservative), does not assume normality of sampling distribution,
and tends to be more accurate (Hayes, 2013). The process mediation model is also
preferable to the Baron and Kenny (1986) approach because it quantifies the indirect effect
and uses an inferential test, it is more powerful, it does not require that the independent
variable affects the dependent variable, and it allows quantification and comparison of
different indirect effects (Hayes, 2013).
Selection of control variables. Control variables were selected based on
demographic factors that are related to the outcome variables of interest. Age, gender, and
cognitive functioning (IQ) were controlled for in research questions 1-3 due to the
relationship of these demographic factors with anxiety, stigma, and illness cognitions in
the general and epilepsy population (Buelow et al., 2003; Caplan et al., 2005; Caplan et al.,
2008; Caplan et al., 2015; Oguz et al., 2002; Reilly, Atkinson, Chin, et. al., 2015; Schraegle
76
& Titus, 2017a; Williams et al., 2003). Cognitive functioning (IQ) was controlled for in
research question 4 due to its known impact on quality of life in epilepsy (e.g., Conway,
Widjaja, & Smith, 2018).
Research question 1. To what extent do parent factors influence anxiety in youth
with epilepsy?
Analysis for research question 1. To test hypotheses 1a-1c, separate sequential
multiple regression analyses were conducted. The BASC anxiety T-score was regressed on
parent history of psychopathology (positive history or no history) controlling for IQ,
gender, and age, on parent perceptions of stigma (average score) controlling for IQ, gender,
and age, and on parent illness cognitions (total score) controlling for IQ, gender, and age.
Research question 2. To what extent do parent factors mediate the effect of parent
history of psychopathology on anxiety in youth with epilepsy?
Analysis for research question 2. To test hypotheses 2a and 2b, mediations were
assessed with a bias-corrected bootstrap confidence interval using the PROCESS macro
(Hayes, 2013) to determine the indirect effect of parent history of psychopathology on the
BASC anxiety T-score through parent perceptions of stigma (average score), controlling
for IQ, gender, and age, and through parent illness cognitions (total score), controlling for
IQ, gender, and age.
Research question 3. To what extent does seizure severity influence the impact of
parent factors on anxiety in youth with epilepsy?
77
Analysis for research question 3. To test hypotheses 3a and 3b, moderation was
assessed with a simple moderation model using the PROCESS macro (Hayes, 2013). The
PROCESS model generated the conditional effects of parent history of psychopathology
on parent perceptions of stigma at varying levels of seizure severity controlling for IQ,
gender, and age and the conditional effects of parent history of psychopathology on parent
illness cognitions at varying levels of seizure severity controlling for IQ, gender, and age.
Research question 4. To what extent do family factors, features of anxiety, and
seizure severity influence quality of life in youth with epilepsy?
Analysis for research question 4. To test hypothesis 4, a simultaneous multiple
regression analysis was conducted. Total HRQOL was regressed on seizure severity,
anxiety, parent perceptions of stigma, and parent illness cognitions controlling for IQ.
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Chapter 4: Results
The purpose of this study was to examine parent reported anxiety in pediatric
epilepsy and the role of seizure severity, parent history of psychopathology, parent illness
cognitions, and parent perceptions of stigma as well as the impact of these variables on
Health-Related Quality of Life (HRQOL). All statistical analyses were performed using
SPSS (version 22.0).
Preliminary Data Analysis
Descriptive statistics. Descriptive statistics regarding demographic characteristics,
such as IQ, age at evaluation, gender, race/ethnicity, parent history of psychopathology,
and maternal education can be found in Table 1. Youth were between the ages of 6 and 18
(M=12.43; SD=3.76). A slight majority of patients were female (57%). IQ scores ranged
from 40 to 123 (M=78.08; SD=18.53). 28.9% of youth with epilepsy had a parent with a
history of psychopathology.
79
Table 1: Demographic characteristics.
n (%) Mean (SD) IQ -- 78.08 (18.53) Age -- 12.43 (3.76) Gender
Female 69 (57) -- Male 52 (43) --
Race/Ethnicity White, Non-Hispanic 58 (47.9) -- White, Hispanic 30 (24.8) -- Black/African American 8 (6.6) -- Asian/Asian American 5 (4.1) -- Other 9 (7.4) -- Missing/Decline to state 11 (9.1) --
Parent history of psychopathology Absent 83 (68.6) -- Present 35 (28.9) --
Maternal Education < High school degree 5 (4.1) -- High school degree 26 (21.5) -- Some college 28 (23.1) -- College degree 33 (27.3) -- Graduate degree 15 (12.4) --
Descriptive statistics regarding epilepsy characteristics can be found in Table 2.
Epilepsy age of onset ranged from infancy to 16 years (M=5.90; SD=4.62). Duration of
epilepsy ranged from 2 months to 18 years (M=6.57; SD=4.27). The seizure severity
composite ranged from 0 to 9 (M=4.83, SD=2.43). Most youth were on polytherapy
(47.9%) or monotherapy (39.7%) antiepileptic drug treatment. A majority of youth
experienced focal epilepsy (49.6%) and 26 patients (21.5%) did not experience a seizure
in the past year.
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Table 2: Epilepsy characteristics.
n (%) Mean (SD) Age of onset (years) -- 5.90 (4.62) Duration (years) -- 6.57 (4.27) Seizure severity -- 4.83 (2.43) Antiepileptic drug type
None 15 (12.4) -- Monotherapy 48 (39.7) -- Polytherapy 58 (47.9) --
Intractability status Intractable 65 (53.7) -- Not intractable 56 (46.3) --
Epilepsy type No seizures in past year 26 (21.5) -- Absence 10 (8.3) -- Focal 60 (49.6) -- Generalized tonic-clonic 21 (17.4) -- Multiple seizure types 4 (3.3) --
Seizure frequency None in past year 26 (21.5) -- Yearly 12 (9.9) -- Quarterly 49 (40.5) -- Weekly or daily 34 (28.1) --
Descriptive statistics regarding the different parent reported measures can be found
in Table 3. On the BASC, 21 parents endorsed anxiety features in the at-risk range for their
child (T-scores 60-69; 17.4%) and 10 parents endorsed anxiety features in the clinically
significant range for their child (T-scores ³70; 8.3%). T-scores on the BASC Anxiety scale
ranged from 32 to 82, with mean scores in the average range (M=52.60; SD=10.77). Parent
perceptions of stigma ranged from 1 to 4 (M=2.44; SD=0.88). Total illness cognitions
scores ranged from 42 to 72 (M=62.16; SD=6.65). Quality of life scores ranged from 20.25
to 93.95 (M=62.72; SD=15.65).
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Table 3: Parent reported questionnaires.
n (%) Mean (SD) Anxiety -- 52.60 (10.77)
At-risk 21 (17.4) -- Clinically significant 10 (8.3) --
Stigma -- 2.44 (0.88) Illness Cognitions Total -- 62.16 (6.65)
Acceptance -- 20.83 (2.95) Helplessness -- 8.95 (2.77) Perceived benefits -- 20.28 (3.85)
Quality of Life Total -- 62.72 (15.65) Cognitive -- 49.67 (20.16) Emotional -- 72.83 (12.90) Social -- 74.98 (24.73) Physical -- 53.30 (22.22)
Table 4 represents the correlation matrix of the outcome variables and all
independent variables of interest.
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Table 4: Correlation matrix.
1. 2. 3. 4. 5. 6. 7. 8. 9. 1. Anxiety 1 -- -- -- -- -- -- -- -- 2. IQ .139 1 -- -- -- -- -- -- -- 3. Age .032 .086 1 -- -- -- -- -- -- 4. Gender .128 .033 .056 1 -- -- -- -- -- 5. Maternal education -.015 -.192* -.026 -.007 1 -- -- -- -- 6. Parent history .204* .102 .019 -.006 -.038 1 -- -- -- 7. Stigma .190* -.237** .089 -.066 .038 .101 1 -- -- 8. Illness cognitions -.131 -.041 -.127 -.078 -.249** -.081 -.251** 1 -- 9. Seizure severity .019 -.297** .100 .134 .028 -.062 .384** -.190* 1 10. Quality of life -.219* .376** .060 -.006 .094 -.113 -.569** .292** -.432**
*p<.05; **p<.01
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Assumptions. The data were examined for any violations of assumptions required
for multiple regression. Inspection of frequency distributions, histograms, Cook’s
Distance, and box plots yielded no outliers. Assumptions of normality, linearity, and
homoscedasticity were visually assessed and confirmed using residual scatter plots.
Normal distribution of the residuals was confirmed via q-q plots of predicted and observed
values. Multicollinearity was assessed with tolerance and variance inflation factors, which
were within normal limits.
Main Analyses
Research question 1. Parent history of psychopathology, elevated parent
perceptions of stigma, and negative parent illness cognitions were expected to be related
to increased parent reported anxiety features in youth with epilepsy. To test hypotheses 1a-
1c, separate sequential multiple regression analyses were conducted. The p-value
associated with the change in R2 was examined at an alpha level of 0.017 (using the
Bonferroni correction to adjust for multiple comparisons and a family-wise error rate of
.05).
Hypothesis 1a. Parent history of psychopathology was expected to account for a
significant amount of variance in parent reported child anxiety among pediatric epilepsy
patients after controlling for gender, age, and IQ. Model statistics for all variables can be
found in Table 5. IQ, gender, and age accounted for 5.3% of the variance in parent reported
child anxiety, but none of the control variables contributed significantly to the overall
model, F(3, 113) = 2.132, p = .100. When added to the model, parent history of
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psychopathology accounted for 3.5% of the variance in parented reported child anxiety,
but the change in R2 did not reach statistical significance after controlling for multiple
comparisons, F Change (1, 113) = 4.356, p=.039. The semipartial correlation of parent
reported child anxiety with parent history of psychopathology was .187. This finding
suggests that parent history of psychopathology did not contribute uniquely to the model.
Table 5: Parent history of psychopathology regression model.
B SE B b p R2 ΔR2 Block 1 -- -- -- .100 .053 .053
Constant 42.301 5.165 -- .000 -- -- IQ .105 .053 .182 .050 -- -- Age -.001 .258 .000 .996 -- -- Gender 2.903 1.962 .135 .142 -- --
Block 2 -- -- -- .032 .088 .035 Constant 41.915 5.094 -- .000 -- -- IQ .094 .053 .163 .076 -- -- Age -.007 .254 -.002 .979 -- -- Gender 2.947 1.93 .137 .130 -- -- Parent Hx Psych 4.376 2.097 .188 .039 -- --
Note: p-value for Blocks 1 and 2 is the significance of the overall model F statistic
Hypothesis 1b. Parent perception of stigma was expected to account for a
significant amount of variance in parent reported child anxiety among pediatric epilepsy
patients after controlling for gender, age, and IQ. Model statistics for all variables can be
found in Table 6. IQ, gender, and age accounted for 3.5% of the variance in parent reported
child anxiety, but none of the control variables contributed significantly to the overall
model, F(3, 117) = 1.397, p = .247. When added to the model, parent perception of stigma
accounted for 5.6% of the variance in parented reported child anxiety, and the change in
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R2 was statistically significant, F Change (1, 116) = 7.153, p=.009. The semipartial
correlation of parent reported child anxiety with parent perception of stigma was .237. This
finding suggests that parent perceptions of stigma may uniquely contribute parent reported
child anxiety features, even when demographic variables known to adversely impact child
anxiety are taken into account. Parents who believe that their children are stigmatized due
to their epilepsy also rate more features of anxiety in their children.
Table 6: Stigma regression model.
B SE B b p R2 ΔR2 Block 1 -- -- -- .247 .035 .035
Constant 44.522 5.199 -- .000 -- -- IQ .078 .053 .134 .146 -- -- Age .040 .262 .014 .878 -- -- Gender 2.651 1.972 .122 .181 -- --
Block 2 -- -- -- .025 .091 .056 Constant 35.268 6.136 -- .000 -- -- IQ .113 .053 .194 .037 -- -- Age -.040 .257 -.014 .878 -- -- Gender 2.992 1.927 .138 .123 -- -- Stigma 3.000 1.122 .246 .009 -- --
Note: p-value for Blocks 1 and 2 is the significance of the overall model F statistic
Hypothesis 1c. Parent illness cognitions were expected to account for a significant
amount of variance in parent reported child anxiety among pediatric epilepsy patients after
controlling for gender, age, and IQ. Model statistics for all variables can be found in Table
7. IQ, gender, and age accounted for 3.5% of the variance in parent reported child anxiety,
but none of the control variables contributed significantly to the overall model, F(3, 117)
= 1.397, p = .247. When added to the model, parent illness cognitions accounted for 1.3%
of the variance in parented reported child anxiety, but the change in R2 did not reach
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statistical significance after controlling for multiple comparisons, F Change (1, 116) =
1.612, p=.207. The semipartial correlation of parent reported child anxiety with parent
illness cognitions was .114. This finding suggests that parent illness cognitions did not
contribute uniquely to the model.
Table 7: Illness cognitions regression model.
B SE B b p R2 ΔR2 Block 1 -- -- -- .247 .035 .035
Constant 44.522 5.199 -- .000 -- -- IQ .078 .053 .134 .146 -- -- Age .040 .262 .014 .877 -- -- Gender 2.651 1.972 .122 .181 -- --
Block 2 -- -- -- .220 .048 .013 Constant 56.981 11.098 -- .000 -- -- IQ .076 .053 .130 .155 -- -- Age .000 .263 .000 1.000 -- -- Gender 2.475 1.972 .114 .212 -- -- Illness cognitions -.188 .148 -.116 .207 -- --
Note: p-value for Blocks 1 and 2 is the significance of the overall model F statistic
Research question 2. Parent perceptions of stigma and parent illness cognitions
were expected to partially mediate the effect of parent history of psychopathology on parent
reported anxiety features in youth with epilepsy. To test hypotheses 2a and 2b, mediations
were assessed with a bias-corrected bootstrap confidence interval using the PROCESS
macro (Hayes, 2013). The 95% bias-corrected bootstrap confidence intervals were
examined, and if they did not include zero the indirect effect was considered statistically
significant.
Hypothesis 2a. Parent perception of stigma was expected to mediate the relation
between parent history of psychopathology and parent reported child anxiety after
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controlling for gender, age, and IQ. The 95% bias-corrected bootstrap confidence interval
of the indirect effect contained zero and was not significant (95% CI: -.6734 - 2.0633), see
Table 8. This finding suggests that there is not a significant indirect effect of parent history
of psychopathology on the BASC anxiety T-score through parent perceptions of stigma.
Table 8: Stigma mediation model.
Effect SE* t p LLCI* ULCI* Total effect 4.4317 2.2807 1.9431 .0546 -.0887 8.9520
Direct effect 3.9537 2.2220 1.7793 .0780 -.4507 8.3582 Indirect effect .4780 .6674 -- -- -.6734 2.0633
*Indirect effect values show the bootstrapped SE and confidence intervals. LLCI=lower limit of CI; ULCI=upper limit of CI.
Hypothesis 2b. Parent illness cognitions were expected to mediate the relation
between parent history of psychopathology and parent reported child anxiety after
controlling for gender, age, and IQ. The 95% bias-corrected bootstrap confidence interval
of the indirect effect contained zero and was not significant (95% CI: -.2295 - .9254), see
Table 9. This finding suggests that there is not a significant indirect effect of parent history
of psychopathology on the BASC anxiety T-score through parent illness cognitions.
Table 9: Illness cognitions mediation model.
Effect SE* t p LLCI* ULCI* Total effect 4.4317 2.2807 1.9431 .0546 -.0887 8.9520
Direct effect 4.3905 2.2874 1.9194 .0576 -.1436 8.9245 Indirect effect .0412 .2405 -- -- -.2295 .9254
* Indirect effect values show the bootstrapped SE and confidence intervals. LLCI=lower limit of CI; ULCI=upper limit of CI.
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Research question 3. Seizure severity was expected to moderate the possible effect
of parent history of psychopathology on parent perceived stigma and on parent illness
cognitions. To test hypotheses 2a and 2b, moderation was assessed with a simple
moderation model using the PROCESS macro (Hayes, 2013). The 95% bias-corrected
bootstrap confidence intervals were examined, and if they did not include zero the
interaction was considered significant.
Hypothesis 3a. Seizure severity was expected to moderate the possible effect of
parent history of psychopathology on parent perception of stigma after controlling for
gender, age, and IQ. The 95% bias-corrected bootstrap confidence interval of the
interaction contained zero and was not significant, p=.7091, see Table 10. This finding
suggests that seizure severity does not moderate the relation between parent history of
psychopathology and parent perception of stigma.
Table 10: Effect of parent history on stigma at varying levels of seizure severity.
Effect/coeff SE t p LLCI ULCI R2**
Interaction model -.0304 .0812 -.3740 .7091 -.1914 .1306 .0011 Low severity .2572 .2499 1.0292 .3057 -.2382 .7527 -- Medium severity .1851 .1844 1.0036 .3178 -.1805 .5506 -- High severity .1129 .2828 .3992 .6906 -.4478 .6735 --
*Low severity=2.5275; Medium severity=4.9035; High severity=7.2795 ** R2 is the increase in R2 due to the interaction
Hypothesis 3b. Seizure severity was expected to moderate the possible effect of
parent history of psychopathology on parent illness cognitions after controlling for gender,
age, and IQ. The 95% bias-corrected bootstrap confidence interval of the interaction
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contained zero and was not significant, p=.8047, see Table 11. This finding suggests that
seizure severity does not moderate the relation between parent history of psychopathology
and parent illness cognitions.
Table 11: Effect of parent history on illness cognitions at varying levels of seizure severity.
Effect/coeff SE t p LLCI ULCI R2**
Interaction model -.1559 .6288 -.2479 .8047 -1.4024 1.0906 .0005 Low severity -.2790 1.9354 -.1441 .8857 -4.1157 3.5577 -- Medium severity -.6494 1.4278 -.4548 .6502 -3.4799 2.1811 -- High severity -1.0199 2.1900 -.4657 .6424 -5.3612 3.3215 --
* Low severity=2.5275; Medium severity=4.9035; High severity=7.2795 ** R2 is the increase in R2 due to the interaction
Additional analysis. To further understand the effects of stigma and seizure
severity on parent reported anxiety, an additional post-hoc exploratory analysis was
completed. Seizure severity was expected to moderate the effect of parent perceived stigma
on parent reported child anxiety after controlling for gender, age, and IQ. The 95% bias-
corrected bootstrap confidence interval of the interaction was significant, p=.0302, see
Table 12. This finding suggests that there is an interaction between parent perceived stigma
and seizure severity on parent reported child anxiety. As shown in Figure 7, at low levels
of seizure severity (2.4045) there is not a significant relation between parent perceived
stigma and parent reported child anxiety, p=.8062. However, at medium (4.8347) and high
(7.2649) levels of seizure severity, there is a significant relation between parent perceptions
of stigma and parent reported child anxiety (p=.0091 and p=.0008, respectively). This
suggests that in parents of children with higher seizure severity, parents who believe their
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child is stigmatized rate higher features of anxiety in their children, while parents of
children with high seizure severity who perceive less stigma rate lower features of anxiety
in their children. In parents of children with low seizure severity, parent perceptions of
stigma are not related to their ratings of anxiety in their children.
Table 12: Effect of stigma on anxiety at varying levels of seizure severity.
Effect/coeff SE t p LLCI ULCI R2**
Interaction model 1.1119 .5066 2.1949 .0302 .1084 2.1154 .0368 Low severity .4239 1.7237 .2460 .8062 -2.9906 3.8385 -- Medium severity 3.1260 1.1787 2.6520 .0091 .7909 5.4611 -- High severity 5.8280 1.6849 3.4590 .0008 2.4903 9.1657 --
*Low severity=2.4045; Medium severity=4.8347; High severity=7.2649 ** R2 is the increase in R2 due to the interaction
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Figure 7: Effect of stigma on anxiety at varying levels of seizure severity. This figure represents the interaction between seizure severity and parent perceptions of stigma on parent reported child anxiety. The blue dots and line represent parent ratings of children with low seizure severity (ratings between 0 and 4; n= 35). The green dots and line represent parent ratings of children with medium seizure severity (ratings between 5 and 6; n= 55). The orange dots and line represent parent ratings of children with high seizure severity (ratings between 6 and 9; n= 31).
Research question 4. Seizure severity, parent reported anxiety, parent perceptions
of stigma, and parent illness cognitions were expected to account for a significant amount
of variance in HRQOL among youth with epilepsy after controlling for IQ. To test research
question 4, a simultaneous multiple regression analysis was conducted. The p-value of the
regression coefficient associated with the variable of interest was examined at an alpha
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level of 0.05. The regression model was statistically significant, F(5, 115) = 20.170, p =
.000, and accounted for 46.7% of the variance in parent reported quality of life (R2 = 0.467,
adj R2 = 0.444). Model statistics for all predictor variables can be found in Table 13. These
results indicate that that stigma, parent illness cognitions, and parent reported child anxiety
all uniquely contribute to HRQOL, even when IQ and seizure severity are taken into
account.
Table 13: Health-related quality of life regression model.
B SE B b p R2
Overall model -- -- -- .000** .467 Constant 56.539 14.574 -- .000** -- IQ .223 .062 .264 .001** -- Seizure severity -1.163 .492 -.180 .020* -- Stigma -6.512 1.381 -.367 .000** -- Illness cognitions .366 .168 .155 .032* -- Anxiety -.236 .103 -.163 .023* --
*p<.05; **p<.01
Additional analysis. To further understand the role of these variables on HRQOL,
additional exploratory simultaneous multiple regression analyses were completed for each
subscale of the QOLCE-55.
Cognitive. The regression model for the cognitive domain was statistically
significant, F(5, 115) = 5.487, p = .000, and accounted for 19.3% of the variance in parent
reported quality of life in the cognitive domain (R2 = .193, adj R2 = .158). Model statistics
can be found in Table 14. These results indicate that parent reported child anxiety
contributes to parent reported quality of life in the cognitive domain, even after accounting
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for the child’s IQ. Parents who reported higher levels of child anxiety reported lower
quality of life in the cognitive domain for their child.
Table 14: Health-related quality of life cognitive domain regression model
B SE B b p R2
Cognitive domain model -- -- -- .000** .193 Constant 23.753 23.110 -- .306 -- IQ .405 .099 .372 .000** -- Seizure severity .262 .781 .032 .738 -- Stigma -2.396 2.189 -.105 .276 -- Illness cognitions .265 .267 .087 .324 -- Anxiety -.334 .163 -.179 .043* --
*p<.05; **p<.01
Emotional. The regression model for the emotional domain was statistically
significant, F(5, 115) = 10.694, p = .000, and accounted for 31.7% of the variance in parent
reported quality of life in the emotional domain (R2 = .317, adj R2 = .288). Model statistics
can be found in Table 15. These results indicate that parent perceptions of stigma and parent
illness cognitions contribute to parent reported quality of life in the emotional domain, even
after accounting for parent reported child anxiety and intelligence. Parents who reported
higher perceptions of stigma and more negative illness cognitions reported lower quality
of life in the emotional domain for their child.
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Table 15: Health-related quality of life emotional domain regression model
B SE B b p R2
Emotional domain model -- -- -- .000** .317 Constant 61.801 13.599 -- .000** -- IQ .116 .058 .166 .049* -- Seizure severity .063 .459 .012 .891 -- Stigma -4.093 1.288 -.280 .002** -- Illness cognitions .463 .157 .239 .004** -- Anxiety -.325 .096 -.271 .001** --
*p<.05; **p<.01
Social. The regression model for the social domain was statistically significant, F(5,
115) = 17.095, p = .000, and accounted for 42.6% of the variance in parent reported quality
of life in the social domain (R2 = .426, adj R2 = .401). Model statistics can be found in Table
16. These results indicate that parent perceptions of stigma and seizure severity contribute
to parent reported quality of life in the social domain. Parents who reported higher
perceptions of stigma reported lower quality of life in the social domain for their child.
Table 16: Health-related quality of life social domain regression model
B SE B b p R2
Social domain model -- -- -- .000** .434 Constant 105.785 23.889 -- .000** -- IQ .121 .102 .091 .238 -- Seizure severity -3.361 .807 -.330 .000** -- Stigma -9.735 2.263 -.348 .000** -- Illness cognitions .274 .276 .074 .322 -- Anxiety -.329 .169 -.143 .054 --
*p<.05; **p<.01
Physical. The regression model for the physical domain was statistically
significant, F(5, 115) = 14.712, p = .000, and accounted for 39% of the variance in parent
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reported quality of life in the physical domain (R2 = .390, adj R2 = .364). Model statistics
can be found in Table 17. These results indicate that intelligence, parent perceptions of
stigma, and seizure severity all contribute to parent reported quality of life in the physical
domain. Parents reported lower quality of life in the social domain if their child had a lower
IQ, more severe seizures, or if the parent reported higher perceptions of stigma.
Table 17: Health-related quality of life physical domain regression model
B SE B b p R2
Physical domain model -- -- -- .000** .390 Constant 31.684 22.137 -- .155 -- IQ .261 .095 .217 .007** -- Seizure severity -1.521 .748 -.166 .044* -- Stigma -9.791 2.097 -.389 .000** -- Illness cognitions .481 .256 .144 .063 -- Anxiety .050 .156 .024 .748 --
*p<.05; **p<.01
Summary
Research question 1 examined the extent that parent factors influenced parent
reported anxiety in youth with epilepsy. Findings suggested that parent illness cognitions
and parent history of psychopathology did not predict parent reported child anxiety after
controlling for gender, age, and IQ. However, parents who believed their children
experienced more stigma related to their epilepsy rated higher anxiety in their children.
Research question 2 examined whether parent factors mediated the possible effect
of parent history of psychopathology on parent reported anxiety in youth with epilepsy.
Parent perceptions of stigma and parent illness cognitions did not mediate the relation
between parent history of psychopathology and parent reported child anxiety.
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Research question 3 examined the extent that seizure severity interacted with
parent factors to influence parent reported anxiety in youth with epilepsy. Seizure severity
did not moderate the relation between parent history of psychopathology and parent
perception of stigma and seizure severity did not moderate the relation between parent
history of psychopathology and parent illness cognitions. Additional analysis revealed a
statistically significant interaction between parent perceptions of stigma and seizure
severity. Seizure severity moderated the relation between parent perceptions of stigma and
parent reported child anxiety. At lower levels of seizure severity, there was not a significant
relation between parent perceptions of stigma and parent reported child anxiety. However,
at higher levels of seizure severity, parents who believed their children experienced more
stigma related to their epilepsy also rated higher anxiety in their children.
Research question 4 examined how family factors, parent reported anxiety, and
seizure severity influenced quality of life in youth with epilepsy. Results indicated that
intelligence, seizure severity, parent reported anxiety, parent perceptions of stigma, and
parent illness cognitions were all statistically significant predictors of HRQOL. See Table
18 for a summary of which variables were statistically significant for each domain.
Table 18: Summary of quality of life findings by domain
Cognitive Emotional Social Physical IQ ++ + - ++ Seizure severity - - ++ + Stigma - ++ ++ ++ Illness cognitions - ++ - - Anxiety + ++ - -
+p<.05; ++p<.01; - p>.05
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Chapter 5: Discussion
Summary
Compared to children with other chronic health conditions, youth with epilepsy are
considered to be at the highest risk for anxiety symptoms (Pinquart & Shen, 2011), and
yet, research regarding risk and protective factors for anxiety in youth with epilepsy is
sparse. The purpose of this study was to examine parent reported anxiety in pediatric
epilepsy and the role of seizure severity, parent history of psychopathology, parent illness
cognitions, and parent perceptions of stigma as well as the impact of these variables on
Health-Related Quality of Life (HRQOL). Analyses consisted of a series of sequential and
simultaneous multiple regressions and tests of mediation and moderation using the Hayes
(2013) PROCESS Macro in SPSS version 22.0.
Anxiety. In this sample of referred youth with epilepsy, parent reported anxiety, as
measured by the BASC parent report, was in the average range (mean 52.60; SD 10.77).
Additionally, over 25% of parents reported child anxiety symptoms in the at-risk (17.4%)
or clinically significant (8.3%) range. These results are consistent with rates reported in
other samples of youth with epilepsy (e.g., Titus et al., 2008; Williams et al., 2003) and in
a recent meta-analysis of adults with epilepsy (Scott et al., 2017). It is important to note
that this study relied upon one time parent report of child anxiety. Parents may under-
indentify internalizing problems in children and use of diagnostic interview (e.g., Jones et
al., 2007) has demonstrated higher rates of anxiety in this population. Despite these
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limitations, this study contributes to research characterizing the rates of parent reported
anxiety in youth with epilepsy and confirms the need to further understand the risks and
protective factors involved in the development and maintenance of anxiety in pediatric
epilepsy.
Parent history of psychopathology. In the literature, parent history of
psychopathology is associated with higher risk for anxiety in the general population (e.g.,
Micco et al., 2009) and in the context of pediatric epilepsy (e.g., Jones et al., 2015;
Schraegle & Titus, 2017a). In the current study, after adjusting for multiple comparisons,
parent history of psychopathology did not explain a significant amount of variance in
parent reported child anxiety. This result is unexpected, but it is likely attributable to
limitations in study design. The use of a dichotomous variable and the lower percentage of
parents who reported a history of psychopathology (29%) likely contributed to smaller
power to detect differences than originally calculated in the power analysis.
Parent perceptions of stigma. Stigma has been an overarching hypothesis for
understanding the psychosocial reasons for higher rates of anxiety in the epilepsy
population in comparison to healthy controls and comparable groups with chronic health
conditions (Davies et al., 2003; Hermann et al., 1988). This study replicates previous
findings (Austin, MacLeod, Dunn, Shen, & Perkins, 2004; Austin et al., 2014; Adewuya
& Ola, 2005) and demonstrates that parents who rated higher perceptions of stigma
reported more features of anxiety in their child. This suggests that children who are
stigmatized are more likely to be anxious. Parent perceptions of stigma accounted for
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approximately 5.6% of the variance in parent reported child anxiety, and stigma may play
a small, but important role in the development and maintenance of anxiety in pediatric
epilepsy.
Parent perceptions of stigma may also relate to parent reported child anxiety
indirectly. Perhaps parents who have more perceptions of stigma may also have reduced
perceptions of control. Chorpito and Barlow (1998) suggest that individuals can develop a
psychological vulnerability for anxiety when they perceive events to be outside of their
control after experiencing uncontrollable events (e.g., seizures). Field and Purkis (2011)
theorize that children can acquire fear through verbal information or observations of others.
If parents who perceive high levels of stigma inadvertently model their child’s epilepsy to
be outside of their control, their children may perceive lower levels of control. Previous
research has demonstrated that individuals who perceive lower levels of control report
higher symptoms of anxiety (Gallagher et al., 2014).
Parent perceptions of stigma may also relate to certain parenting behaviors that are
associated with higher anxiety, such as overprotectiveness and accommodation (Anthony
et al., 2003). Previous research has found that higher rates of child anxiety were reported
when parents granted less autonomy to their child (McLeod et al., 2007). Parents who
perceive more stigma may engage in more overprotective parenting to limit their child’s
exposure to this perceived stigmatizing environment. Parents with higher ratings of
perceived stigma may also contribute to their child’s anxiety by socializing them to the
dangers (e.g., stigma) of the outside world (Murray et al., 2009). Parents with higher rates
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of perceived stigma may also be more likely to accommodate their child’s anxiety by
allowing them to avoid anxiety provoking situations. Because this study measured parent
perceptions of stigma, and did not directly measure parenting behaviors, more research is
needed to elucidate the connection between parenting behaviors and perceptions of stigma.
It is also important to consider alternate hypotheses for the relation between parent
perceptions of stigma and parent reported child anxiety. In this model, it was assumed that
parent perceptions of stigma preceded symptoms of parent reported child anxiety.
However, previous research demonstrates the bidirectional relationship of anxiety and
epilepsy, in that anxiety symptoms may precede epilepsy diagnosis (N. C. Jones et al.,
2008). Therefore, it is also likely that in some cases, parent reported child anxiety
symptoms preceded the epilepsy diagnosis and thus also preceded parent formation of
perceptions of stigma. In these scenarios, parent perceptions of stigma may maintain or
exacerbate parent reported anxiety symptoms. While the questions on the epilepsy stigma
scale are placed in the context of epilepsy, parents of youth with epilepsy and anxiety may
also be more likely to perceive higher levels of stigma. Furthermore, parents who rate
higher perceptions of stigma may also be more inclined to rate their child’s anxiety as more
severe. It may be difficult to disentangle parent reported perceptions of stigma with parent
reported child anxiety, and future research should collect anxiety and stigma ratings
through different sources (e.g., child, teacher) and methods (e.g., diagnostic interview,
observation).
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Parent perceptions of stigma were also hypothesized to mediate the relation
between parent history of psychopathology and parent reported child anxiety. However,
this study did not find a statistically significant indirect effect; this is likely attributable to
the smaller sample of parents with a history of psychopathology than originally anticipated.
Additionally, this study used parent history of psychopathology, and not current levels of
psychopathology or distress. Future research should measure current levels of parent
psychopathology or distress.
Parent illness cognitions. It was hypothesized that more negative parent illness
cognitions would be associated with higher parent reported anxiety symptoms. This current
research did not support this hypothesis. This result was unexpected because previous
research demonstrates that negative illness cognitions regarding a child’s illness is related
to parent distress, which, in turn, is related to more emotional distress in children (Colletti
et al., 2008; Nicolaas et al., 2016; Robinson et al., 2007; Steele et al., 2004). While the
Illness Cognitions Questionnaire measures an aspect of a parent’s coping and adjustment
to their child’s illness, illness cognitions are just one component of coping. Future research
may wish to examine other aspects of parent coping and explore the relation between parent
illness cognitions or coping and parenting behaviors.
It was also hypothesized that parent illness cognitions would mediate the relation
between parent history of psychopathology and parent reported child anxiety. However,
this study did not find a statistically significant indirect effect. This is likely attributable to
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the previous finding that parent illness cognitions were not associated with higher parent
reported anxiety symptoms.
Seizure severity. Epilepsy variables have been consistently explored as possible
causes of higher rates of anxiety in pediatric epilepsy. In this study, seizure severity was
examined as a variable that may interact with other psychosocial variables. It was
hypothesized that seizure severity would moderate the effect of parent history of
psychopathology on parent perceived stigma (i.e., in the context of low seizure severity,
parents with a history of psychopathology would report higher levels of perceived stigma,
but in the context of high seizure severity, both parents with and without a history of
psychopathology would report high levels of perceived stigma (see Figure 3)). A similar
interaction was hypothesized for parent illness cognitions, in that seizure severity would
moderate the effect of parent history of psychopathology on parent illness cognitions (see
Figure 4). In both models, there was no interaction between parent history of
psychopathology and seizure severity.
This finding suggests that the relation between parent history of psychopathology
and parent illness cognitions and parent perceptions of stigma is not dependent on seizure
severity. While an interaction was hypothesized, this finding is not completely unexpected
because moderation effects are rare (Keith, 2014). This study may not have been
adequately powered to detect a moderation effect when using a dichotomous variable for
parent history of psychopathology. Additionally, parent illness cognitions and parent
perceptions of stigma may be more dependent upon current levels of parent distress, and
103
not history of psychopathology. Future research should examine the effect of seizure
severity on parent perceptions of stigma and illness cognitions in the context of current
parent distress due to its relation to emotional distress in the child (Colletti et al., 2008;
Nicolaas et al., 2016; Robinson et al., 2007; Steele et al., 2004).
To further explore the effect of seizure severity on parent perceptions of stigma and
parent reported child anxiety, a post hoc exploratory analysis was completed. Seizure
severity was hypothesized to moderate the relation between parent perceptions of stigma
and parent reported child anxiety. Results demonstrated that there was an interaction
between parent perceptions of stigma and seizure severity on parent reported child anxiety
(see Figure 7). This finding suggests that there is a conditional effect of parent perceptions
of stigma on parent reported child anxiety at varying levels of seizure severity. In other
words, at low levels of seizure severity, there was not a relation between parent perceptions
of stigma and parent reported child anxiety. However, at higher levels of seizure severity,
parents with more perceptions of stigma also reported higher levels of child anxiety.
There are several reasons why this interaction between seizure severity and parent
perceptions of stigma may occur. First, in the literature it has been demonstrated that higher
seizure severity is associated with higher perceptions of stigma (Austin et al., 2014).
Epilepsy is more visible in children with more severe seizures, and perhaps perceptions of
stigma may be more internalized in these youth. Youth with greater seizure severity may
be more susceptible to experiencing stigma related to their epilepsy, and therefore are more
likely to develop anxiety. The importance of the context of high seizure severity is
104
supported by Gandy et al. (2012), who hypothesized that stigma might be more important
in individuals with poorly controlled epilepsy, while stigma is less important for
individuals with epilepsy who have less frequent seizures.
The interaction between parent perceptions of stigma and seizure severity may also
indirectly affect parent reported anxiety through parenting behaviors. Parents who perceive
high stigma may engage in more over-protective parenting, particularly when their child’s
seizures are more severe. In contrast, low parent perceptions of stigma in parents of
children with high seizure severity may be a protective factor for children. These parents
with lower perceptions of stigma may model higher perceptions of control and may not be
as over-protective. In contrast, parents of children with lower seizure severity may not need
to engage in as much over-protective parenting. More research is needed to determine if
parenting behaviors change in the context of higher seizure severity along varying levels
of perceived stigma.
It is also important to consider alternate hypotheses and note that perceptions of
stigma and child anxiety were measured through parent report. Perhaps parents with
children with more severe epilepsy rated more perceived stigma when their child had
symptoms of anxiety. Alternatively, parents of children with high seizure severity who
rated higher perceived stigma may also be more likely to rate more features of anxiety.
Furthermore, perhaps in the context of lower levels of seizure severity, parents may not
perceive as much stigma towards their child’s epilepsy, and therefore there is not enough
variability in stigma to predict parent reported child anxiety. However, in the context of
105
high seizure severity, there is more variability in parent perceptions of stigma, and higher
perceived stigma is related to higher parent reported child anxiety.
Quality of life. It is important to consider the impact of family and psychosocial
factors on quality of life in youth with epilepsy. Intelligence, seizure severity, stigma,
parent illness cognitions, and parent reported child anxiety all predicted parent reported
health related quality of life. Additionally, all of the examined variables affected quality of
life differentially across the various domains, see Table 18.
As demonstrated in previous research, parent reported anxiety is related to lower
quality of life in youth with epilepsy (Baca et al., 2011; Loiselle et al., 2016; Puka & Smith,
2015; Stevanovic et al., 2011). Not surprisingly, lower parent reported anxiety symptoms
were related to better quality of life in the emotional domain. Many questions in the
emotional domain relate to symptoms of anxiety (e.g., worry) and depression, so there is
some construct overlap within this domain. However, parent reported anxiety was also an
important predictor of health-related quality of life in the cognitive domain, even after
accounting for the child’s IQ. A recent meta-analysis suggests that anxiety impacts
cognitive functioning, particularly working memory (Moran, 2016). This research
demonstrates the need to address anxiety in order to improve a child’s quality of life.
Parent perception of stigma was an important predictor of total health related
quality of life, as well as quality of life in the emotional, social, and physical domains. In
the emotional domain, parents who perceived their child as more stigmatized because of
their epilepsy reported poorer quality of life in areas such as feeling valued and understood.
106
Parent perception of stigma was also an important predictor of quality of life in the social
domain. The social domain also captures certain aspects of stigma, such as feelings of
isolation and frightening others, which may demonstrate some construct overlap. However,
children with epilepsy may also have difficulty participating in social activities (Institute
of Medicine, 2012) and this may be compounded when they are also experiencing stigma.
Finally, parent perception of stigma was a significant predictor of quality of life in the
physical domain. Parents with more perceptions of stigma may engage in more
overprotective parenting, such as limiting or restricting their child’s physical activities or
social interactions.
Parent illness cognitions were a significant predictor of overall quality of life and
more positive parent illness cognitions were related to improved quality of life in the
emotional domain. Interestingly, parent illness cognitions were related to emotional quality
of life, but not parent reported child anxiety. Perhaps parent illness cognitions are related
to broader aspects of emotional functioning captured on the quality of life measure, such
as depression and oppositional behaviors.
It is noteworthy that seizure severity was only a significant predictor of quality of
life in the physical and social domains. This aligns with other research in pediatric epilepsy
and research on outcomes of epilepsy surgery that demonstrate that seizure outcomes are
only significant predictors of quality of life in the physical and social domains (Conway,
Widjaja, & Smith, 2018; Schraegle & Titus, 2016; Titus et al., 2013). This suggests that
while improving seizure outcomes is important, other psychosocial factors, such as anxiety,
107
cognitive functioning, parent illness cognitions, and parent perceptions of stigma, need to
be addressed in order to improve quality of life in youth with epilepsy. Taken together,
these findings suggest the multitude of psychosocial factors that are important to quality of
life in youth with epilepsy.
Limitations
While this research demonstrates the importance of parent factors on parent
reported child anxiety in youth with epilepsy, there are also several limitations to consider.
First, it is important to note the limited generalizability of these findings as well as the
representativeness of this sample for the epilepsy population. This research was conducted
with a clinically referred group of youth with epilepsy. These patients were under
consideration for epilepsy surgery and/or demonstrated a need for a neuropsychological
evaluation. Therefore, these patients may represent a sample of youth with more severe
epilepsy. Additionally, while this research controlled for the effects of intelligence, this
sample of youth had a lower mean IQ (78) than the mean IQ (84.96) reported in a recent
population-based sample of youth with epilepsy (Reilly, Atkinson, Das, et al., 2015a). The
results of this paper should be considered in the context of this more severe patient
population and may not be representative of the overall epilepsy community.
As discussed previously, this research relied upon a dichotomous variable for
parent history of psychopathology. The use of a dichotomous variable limits the power of
understanding the effects of parent psychopathology on child outcomes. Additionally, this
108
variable was based off of parent report, which might be prone to social desirability bias.
Finally, while use of history of psychopathology may be useful in understanding the
genetic component of anxiety, current psychopathology or parent distress would be more
helpful in understanding how current emotional distress in the parent affects child
outcomes.
It is also important to consider that this study relied upon the use of parent reported
measures of anxiety. Research demonstrates that parents under-report internalizing
psychopathology and that parent and child ratings are only modestly correlated
(Achenbach, McConaughy, & Howell, 1987). This suggests that both parent and child
ratings may need to be considered in order to more fully understand the emotional state of
the child. Furthermore, this research relied upon measures of parent perceptions of various
constructs and not direct measures of parent behaviors. It is unclear whether parent
perceptions of stigma and parent illness cognitions are directly related to parenting
behaviors, such as overprotectiveness and accommodation.
Additionally, this research is cross-sectional in nature, limiting the understanding
of temporal precedence. It has been hypothesized that epilepsy and anxiety have a
bidirectional relationship and as mentioned previously, symptoms of anxiety may precede
the diagnosis of epilepsy. This study is also limited by the fact that it did not include a
control group comparison.
Finally, while it was helpful to represent seizure severity as one variable, this also
limits the interpretation of results (e.g., a score of a 5 could represent a child on
109
monotherapy who has daily absence seizures or a child on monotherapy with yearly
generalized tonic-clonic seizures). The use of one variable makes it difficult to interpret
results and make recommendations. Additionally, some constructs, such as age of onset
and intractability status, were not used in the seizure severity variable. Difficulty
quantifying seizure severity is an ongoing issue within epilepsy research, and more effort
is needed to fully understand the best way to conceptualize this construct.
Recommendations for research
Future research should address the identified limitations in this study’s design. Use
of a longitudinal analysis in a larger community-based sample might be helpful to elucidate
the temporal precedence of risk and protective factors for anxiety in pediatric epilepsy. A
population-based sample would allow for findings that can be generalized to the general
epilepsy population and use of a larger sample size would also allow stratification based
on variables known to be associated with anxiety, including age, gender, and IQ.
There are also several ways limitations in measurement may also be addressed. In
this study, anxiety was measures through the use of the BASC parent report. The BASC is
typically a screening tool, so it would be important to use well-validated ratings of anxiety
(e.g., MASC) or semi-structured interviews (e.g., K-SADS) in future research. Use of
multiple informants (e.g., parent, child, clinician) across all measures would demonstrate
whether these findings are similar across different contexts. Additionally, it would be
beneficial to obtain direct measures of parenting behaviors (e.g., overprotectiveness,
accommodation) and psychopathology/emotional distress to further elucidate whether
110
parent perceptions of stigma are directly related to parent behaviors or parent
psychopathology/ emotional distress. Finally, more research is needed to determine the
best way to quantify seizure severity and which seizure-related variables affect
psychosocial outcomes.
More research is needed to understand what factors are related to an increased risk
for anxiety and stigma in order to create modifiable targets for intervention. It would be
interesting to conduct research that may determine whether interventions that help alleviate
perceptions of stigma (e.g., psychoeducation) could reduce anxiety symptoms in youth
with epilepsy. Alternatively, research examining whether treatment of anxiety can lead to
reduced perceptions of stigma may also be beneficial. Use of longitudinal research may
elucidate the temporal precedence of these variables.
While parent illness cognitions were not predictors of parent reported child anxiety
in this study, more research may be needed to demonstrate whether parent illness
cognitions play a role in anxiety in youth with epilepsy. Preliminary evidence from the
emotional domain of health-related quality of life suggests that parent illness cognitions
may be related to other aspects of emotional functioning in the child, such as depression or
behavior difficulties. Future research could use different ways to measure parent coping or
explore the relation between parent and child illness cognitions with other aspects of
psychosocial functioning.
Finally, future research should focus on the relation between parenting behaviors
and child anxiety in epilepsy. While parents may model or verbalize their cognitions and
111
perceptions, parent behaviors, such as over-protectiveness and accommodation, are related
to child anxiety and can be modifiable targets for intervention. Parents of children with
epilepsy could be compared to parents of children with other chronic health conditions to
determine if there are differences in over-protectiveness or limitation of their child’s
activities.
Implications for clinical practice
Neuropsychologists and other clinicians working with youth with epilepsy should
be aware of the higher rates of anxiety within this population and implement screening
procedures to ensure youth with epilepsy are receiving adequate services. Other studies
highlight the lack of children with epilepsy receiving intervention for mental health needs
(Caplan et al., 2005) and clinicians should work to provide appropriate referrals. Cognitive
behavioral therapy, particularly the use of exposure therapy, in combination with
medication management is the ideal treatment for anxiety (Walkup et al., 2008). Clinicians
working with youth with epilepsy who are experiencing anxiety should be aware of the
unique context of epilepsy when delivering intervention. The unpredictable nature of
seizures as well as the social stigma of having seizures may be important targets for
intervention.
Parents may also be an important target for intervention. This current research
suggests that parent perceptions of stigma may play an important role in the development
or maintenance of anxiety. Clinicians may want to work with parents to understand how
these perceptions of stigma may influence how parents interact with and maintain their
112
child’s anxiety. These perceptions of stigma may be particularly important in the context
of more severe epilepsy. Alternatively, if high levels of perceived stigma and high levels
of parent reported child anxiety are artifacts of parent distress and over-reporting, parents
who report high levels of perceived stigma may over-report anxiety symptoms in their
child. Parent reported measures may need to be interpreted in the context of high
perceptions of stigma and high seizure severity.
Finally, it is important for clinicians working with youth with epilepsy and their
families to understand the impact anxiety and other parent factors may have on quality of
life. While seizure severity is generally the target of intervention in pediatric epilepsy
(and is an important aspect of overall quality of life and quality of life in the physical and
social domains) there are other psychosocial variables that impact quality of life. Parent
reported symptoms of anxiety are important predictors of quality of life in the cognitive
and emotional domains and stigma was an important predictor of quality of life across the
social, emotional, and physical domains. This suggests that stigma and anxiety may be
important targets of intervention that can lead to improved quality of life in youth with
epilepsy.
Conclusion
The development of anxiety in pediatric epilepsy is multifactorial, and can be
driven by biological, psychosocial, and environmental factors. The importance of family
factors in the development and maintenance of anxiety is a burgeoning area of research in
pediatric epilepsy. This current work demonstrates the potential for parent perceptions of
113
stigma to play an important role in parent reported anxiety in pediatric epilepsy,
particularly in the context of high seizure severity. More research is needed to understand
the temporal precedence of this relationship (e.g., do parent perceptions of stigma influence
child anxiety, or are more stigmatized perceptions formed in the context of child anxiety?).
Individuals working with youth with epilepsy should be aware of the high rates of parent
reported anxiety and potential role of stigmatization in the development or maintenance of
anxiety.
114
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